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Social Network Analysis and Mining ISSN 1869-5450Volume 3Number 3 Soc. Netw. Anal. Min. (2013) 3:565-595DOI 10.1007/s13278-013-0102-3

Inferring the mental state of influencers

D. B. Skillicorn & C. Leuprecht

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ORIGINAL ARTICLE

Inferring the mental state of influencers

D. B. Skillicorn • C. Leuprecht

Received: 28 November 2012 / Revised: 5 February 2013 / Accepted: 9 February 2013 / Published online: 28 February 2013

� Springer-Verlag Wien 2013

Abstract Most analysis of influence examines the

mechanisms used, and their effectiveness on the intended

audience. Here, we consider influence from another per-

spective: what does the choice in the language of influ-

encers signal about their internal mental state, strategies

and assessments of success? We do this by examining the

language used by the US presidential candidates in the

high-stakes attempt to get elected. Such candidates try to

influence potential voters, but must also pay attention to

the parallel attempts by their competitors to influence the

same pool. We examine channels: nouns, as surrogates

for content; adjectives, verbs, and adverbs as modifiers of

discussion of the same pool of ideas from different per-

spectives, positive and negative language; and persona

deception, the use of language to present oneself as better

than the reality. Several intuitive and expected hypotheses

are supported, but some unexpected and surprising struc-

tures also emerge. The results provide insights into related

influence scenarios where open-source data are available,

e.g., marketing, business reporting, and intelligence.

1 Introduction

We address the problem of language-based influence in

settings where there are a set of influencers and an audience

to be influenced. Some examples of such settings are

shown in Table 1. However, unlike most work on

influence, we do not consider the process from the per-

spective of the audience (how well does it work?) nor from

the perspective of the influencer (how can I do it better?).

Rather we consider what the choices, conscious and sub-

conscious, of the influencer reveal about him/her/them and,

to some extent, how this changes over time. In other words,

we use language to shed light on the influencer’s mind,

rather than as a channel for influence itself. Since choice in

language is partly or completely subconscious, we use

language patterns to access aspects of influencers and their

organizations that may not be obvious—even to

themselves.

Such influencing language cannot realistically be mod-

elled as a one-way channel from influencer to influenced.

An influencer is necessarily concerned with the audience’s

reaction, whether in real-time in a speech, or at longer time

scales using polling or sentiment analysis. Feedback is an

essential part of the process and this should be visible in

longitudinal change.

The main constraints on an influencer are of four dif-

ferent kinds:

1. Intrinsic capabilities, such as linguistic ability and

personality;

2. Goals, the purpose to be served by the communication;

3. Responses, judgements about the effectiveness on the

target audience; and

4. The language of competitors within the same sphere of

influence.

The first three drivers are not very different from those

posited by systemic functional linguists for all communi-

cation (Matthiessen and Halliday 1997; Whitelaw and

Argamon 2004).

We examine the language of influence via eight differ-

ent ‘‘channels’’:

D. B. Skillicorn (&)

School of Computing, Queen’s University, Kingston, Canada

e-mail: [email protected]

C. Leuprecht

School of Policy Studies, Queen’s University, Kingston, Canada

123

Soc. Netw. Anal. Min. (2013) 3:565–595

DOI 10.1007/s13278-013-0102-3

Author's personal copy

1. Nouns, which measure how each influencer chooses

among particular topics to appeal to audience interests

or concerns, and to gain an edge over competitors.

2. Adjective usage, which measures how each influencer

modifies the chosen nouns (if at all). This might also

be an aspect of sentiment since some adjectives have

emotional or polarity associations.

3. Verb usage, which is almost unexplored but which

might measure proactivity versus reactivity, and views

of time encoded in verb tenses.

4. Adverb usage, which measures how each influencer

modifies the chosen verbs and might reveal aspects of

sentiment, e.g., in what way actions are to be taken.

5. Positivity, which measures the attempt to appeal

emotionally to an audience in an uplifting way.

6. Negativity, which measures both openness by the

influencer, and attempts to denigrate competitors.

7. Persona deception, which measures the attempt by

individuals or organizations to appear better, wiser,

smarter, and/or more experienced or more qualified

than they really are.

8. Integrative complexity, which measures the structural

complexity of the way in which ideas are being

communicated. The integrative complexity construct

can be further subdivided into a dialectical aspect, the

extent of awareness that ideas can be understood from

more than one perspective, and an elaborative aspect

that ideas contain internal subtleties that may need to

be developed (Conway et al. 2008).

These channels play different roles in different settings.

For example, businesses use a form of persona deception to

build up their brands, but are rarely negative, even about

competitors. Politicians use persona deception to present

themselves as electable to the position for which they are

campaigning, but are quite willing to be negative about

their competitors. Positivity usually has a self-focus while

negativity almost always has an other-focus.

We assume that what might be called ‘professional’

influencers are well resourced and highly motivated, and

have access to analysis that allows them to assess the extent

to which they are being effective. We also assume that they

have clarity about the goals of their influence that is how

effectiveness is to be defined.

Influencers will be strategic and deliberate about their

use of channels of influence. We are, therefore, particularly

interested when the process of influencing does not seem to

agree with the apparent goals, resources and mechanisms,

and seek explanations for the discrepancies. It might be

that they represent simple failures to carry out a plan, even

if the plan was well-conceived and resourced. But it might

also be that such plans have inherent limits, and that the

humans involved may be unable to act as intended.

We narrow our scope to the contenders for the US

presidential elections of 2008 and 2012 as exemplars of

highly motivated and resourced influencers. Their goals are

comparable to advertisers and insurgents in terms of their

need for effective influence.

The role of influence has been studied extensively in the

context of elections. The functional theory of campaign

discourse (Benoit 2007; Hacker et al. 2000) draws dis-

tinctions between candidates’ policy positions and the

personas that they try to present to audiences, on which we

will draw. An election campaign pursues a strategy to get

their candidate elected. Once this strategy has been

devised, the candidate pursues it; in one sense, the candi-

date represents it. This consistent goal should be obser-

vable in the language patterns used in campaign speeches.

We, therefore, begin with the broad hypothesis:

H1: Candidates will use language consistently over time

in pursuit of their chosen strategy. Of course, there may be

times when the overall strategy is reconfigured. Such times

should be detectable as discontinuities in language patterns.

On a smaller scale, candidates may feel obligated to react

to issues raised by other campaigns, so we expect that there

will be cross-pollination of language patterns between

campaigns.

On the one hand, campaigns also need to differentiate

their candidate from the competing candidates, so we

expect each campaign to settle on particular issues and

perspectives; and possibly also on particular styles of

talking about them. On the other hand, campaigns are also

aware of the issues that matter to voters, and of the need to

appear responsive to them. They must, therefore, balance

the need for differentiation against the need to seem rele-

vant by talking about issues relevant to voters. Our second

broad hypothesis then is:

H2: Candidates will use language that differentiates

them from other candidates but with considerable overlap.

The overlaps will be largest for more-neutral, content-fil-

led, language and less for language relevant to hows and

whys of opinions, policies and actions. In other words,

candidates are forced to talk about the same issues, but

have the opportunity to differentiate themselves on the

basis of process or motivation.

These broad hypotheses suggest that hypotheses about

particular aspects of the way language are used. Benoit has

suggested that candidates need to make their messages

distinctive, but in ways that voters approve (Benoit 2007).

Table 1 Influence settings

Influencer Audience Setting

Businesses Consumers Advertising

Terrorists Sympathizers Recruitment

Politicians Voters Campaigns

566 D. B. Skillicorn, C. Leuprecht

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H3: Nouns differ across candidates, but not greatly

because of the need to discuss issues of interest to all or

most voters.

H4: Verbs, adverbs, and adjectives will show greater

differentiation because they allow candidates to describe

different approaches and styles to common issues.

One part of presenting a candidate or product in the best

possible light is to associate positive feelings with him or

her or it. This suggests:

H5: Candidates will use high levels of positive lan-

guage, both about the future and about themselves.

At the same time, candidates improve their own candi-

dacy by being negative about other candidates. Attacks

reduce the desirability of opponents (Benoit 2004). It is

also widely believed that negative language increases

impact by increasing attention to informational content (but

see Stevens (Stevens 2012) for a discussion of the issues

and a dissenting view). This suggests:

H6: Candidates will use high levels of negative lan-

guage, perhaps directed at their competitors, but perhaps

also painting existing problems as particularly intractable

to position themselves as problem solvers.

Every candidate presents themselves as the best person

for the elected position and, therefore, is motivated to come

across as better than they might actually be. This behavior

is a form of deception: not the factual deception of making

objectively untrue statements, but the persona deception of

putting things in the best possible light (and perhaps by

strategic omission) (Keila and Skillicorn 2005). The same

phenomenon is visible in advertising, where products are

presented in ways that associate them with attributes that

have little to do with the function of the products. This

suggests the hypothesis:

H7: Candidates should show high levels of persona

deception as they try to convince voters that they are well

qualified, and better qualified than their competitors.

Another dimension of campaign language is the level of

sophistication with which each candidate presents and

discusses the issues. This reflects both the candidate’s

ability but also his or her view of the sophistication of the

audience. It has been suggested that voters want simple

cues to assess candidates with minimal effort (Hibbing and

Theiss-Morse 2002). To examine this effect, we use the

integrative complexity construct for which an automated

scoring tool has recently been developed (Conway et al. in

press). A hypothesis for such a construct is not obvious, but

there is some evidence that integrative complexity scores

by presidents reduce as elections draw near. There is also

some evidence that changing integrative complexity is

effective for a candidate when it violates voters’ expecta-

tions, such as when a candidate viewed as naive is able to

deploy high levels of integrative complexity or vice versa

(Conway et al. in press). This suggests:

H8: Candidates reduce their integrative complexity to

signal the crucial binary, us against them, choice and to

make complex issues simpler for voters to understand.

Our overall prediction, therefore, is that candidates who

do better on all of these dimensions are more likely to be

successful.

The contribution of this paper is the exploration of the

mental states of candidates in a highly competitive setting,

with the goal of understanding consistency and variation.

Since consistency seems the most plausible goal, variation

also needs to be explained. We also make some tentative

assessments of which patterns of language use are associ-

ated with success in this domain.

The methodology is also of some interest since it is

lightweight and generalizes to other domains in which

influence is crucial. This approach can be applied to other

open-source influence scenarios where the language used is

available for analysis, including marketing and some kinds

of advertising, business reporting, and intelligence analy-

sis. However, the approach focuses not on the population

segment intended to be influenced, but instead on what can

be learned about the source organizations and individuals.

2 Channels of influence

We consider political speeches, and extract from them

patterns of language use on eight different channels. For

channels based on the rates of occurrence of parts of

speech, we extract document content using the QTagger

(Creasor and Skillicorn 2012), a part-of-speech aware

tagger that uses Lingpipe (Alias-i 2008) as a front-end.

This enables all words tagged as nouns, as adjectives, as

verbs, and as adverbs to be extracted from a set of docu-

ments and their frequencies counted. Positivity and nega-

tivity are computed based on lists of positive and negative

words created by Loughran and McDonald (2011) for

business settings. Since political speeches often have a

significant economic component, these lists were judged to

be more appropriate than the more-general lists used in

sentiment analysis and targeted at consumer products,

books, and movies.

Persona deception—the attempt to appear better than one

is—is a form of deception and is captured well by Penne-

baker’s deception model (Newman et al. 2003). This model

characterizes deception as causing changes in the frequen-

cies of 86 words, in four categories. In deceptive text:

1. First-person singular pronouns (‘‘I’’, ‘‘me’’, ‘‘myself’’)

decrease in frequency;

2. Exclusive words, words that single an increase

in content complexity (‘‘but’’, ‘‘or’’) decrease in

frequency;

Inferring the mental state of influencers 567

123


3. Negative-emotion words (‘‘afraid’’, ‘‘disappointed’’)

increase in frequency;

4. Action verbs (‘‘go’’, ‘‘lead’’) increase in frequency.

Since the meaning of ‘‘increase’’ and ‘‘decrease’’ depends

on some baseline, this model can only be used to rank a

group of cognate documents by their relative deceptive-

ness, not label an individual document as deceptive or not.

For example, in business writing, first-person singular

pronouns are rare, so a mixture of such documents and, say,

blogs would produce non-comparable deceptiveness

scores.

Integrative complexity is a measure of structural intel-

lectual complexity in discussion, argument, or evaluation

(Suedfeld et al. 1992). It is content-neutral and tries to

evaluate the cognitive complexity embodied in a docu-

ment. It has been suggested that integrative complexity

contains two subconstructs, one which evaluates the extent

of awareness of multiple perspectives on any issues (dif-

ferentiation) and the other which evaluates the awareness

of connections between such perspectives (integration).

3 Experimental framework

The campaign speeches of US presidential candidates in

the period from January 2008 to the 2008 election (McC-

ain, Clinton, Obama) and from January 2012 to the 2012

election (Gingrich, Paul, Romney, Santorum, Obama) were

collected. These speeches were, of course, often the

product of many authors, so the insight they provide is

insight into the thinking of each campaign rather than each

candidate. The individuals who delivered each speech do

make alterations on-the-fly and the delivery of speeches

obviously based on the same script differs substantially

from one day to the next—so some insight into individual

speakers is possible. Obama was the only candidate to

participate in both election cycles, but there was consid-

erable overlap of his speechwriters for the two campaigns,

so we do not expect differences between the two cam-

paigns because of changes in personnel.

The complete set of speeches and either a specific word

list or selected parts-of-speech tags were given to the

QTagger which extracted a document-word matrix in

which each entry represents the frequency of (the tagged

version of) each word in each speech. In other words, given

a set of candidate words, say nouns, the result of the

extraction is a matrix with a row corresponding to each

speech, a column corresponding to each word, and whose

entries are the frequencies of each word in each speech.

Each row of the matrix is normalized by dividing by the

row sum to reduce the effect of the difference in lengths

of speeches. Each column of the matrix is normalized to

z scores (subtracting the column mean from each column

entry and dividing by the column standard deviation). As a

result, positive values in the normalized matrix represent

greater than typical rates of use, negative values represent

lower than typical rates of use, while absence and median

use are conflated to small-magnitude entries. This effect is

problematic, although justifiable, and there is no practical

workaround.

In the deception model, the sign of those columns cor-

responding to words where a decrease in frequency is the

signal of an increase in deception are reversed so that

positive entries always correspond to increasing deception.

If the data matrix has n rows (1 per document) and

m columns (1 per word), then each document can be con-

sidered as a point in m-dimensional space. Understanding

of the relationships among documents can be increased by,

e.g., clustering in this space to find groups of similar

documents. (Symmetrically, each word can be considered

as a point in n-dimensional space and the relationships

among words explored by clustering as well.)

However, m is typically large and there are advantages

in projecting the m-dimensional space into one of lower

dimension. Doing so removes some of the noise associated

with polysemy and also makes it possible to visualize the

relationships among the documents.

We do this using singular value decomposition (SVD)

(Golub and van Loan 1996). If A is the data matrix

(n 9 m), then the SVD is given by:

A ¼ USV 0;

where U is n 9 m, S is a diagonal matrix whose entries,

called singular values, are non-increasing, V is m 9 m, and

the superscript dash indicates transposition. Both U and

V are orthogonal matrices.

One interpretation of SVD is that it rotates the space so

that the greatest variation is aligned with the axis given by

the first row of V0, the second-greatest uncorrelated varia-

tion with the second row of V0, and so on. The rows of

U are then the coordinates of each document in this

transformed space.

Because of the ordering of the axes, the decomposition

can be truncated after some k dimensions (a form of pro-

jection) so that

A � UkSkV 0k;

where U is n 9 k, S is k 9 k and V0 is k 9 m. The mag-

nitudes of the singular values indicate how much variation

is captured in each new direction and so estimates how

much is being ignored by truncation at any choice of k. We

use k = 2 and so represent the documents, and words, in a

two-dimensional space. In such a space, different patterns

of word use are reflected by positions in different directions

from the origin—similarity derives from dot products of


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the vectors associated with each point. Distance from the

origin is a measure of the intensity of the difference of the

underlying document or word.

If the data consist of a single underlying factor then the

use of SVD detects this as an almost-linear structure in the

low-dimensional space. Because of the inherent symmetry

between documents and words—if A = USV0 then

A0 = VSU0—points corresponding to both documents and

words can be plotted in the same space (appropriately

scaled). In such a plot, documents can be considered as

being drawn towards the points corresponding to words

that occur within them with higher frequency and, sym-

metrically, words as being drawn to documents in which

they feature. This aids in understanding the relationships

between documents and words. All of the figures are ori-

ented so that the positions of points corresponding to

documents and points corresponding to words are aligned.

4 Results

Throughout this section, the results are coded as shown in

Table 2. In all SVD figures, distance from the origin cor-

responds to increased significance, and directions indicate

different kinds of variation. The axes associated with these

figures are linear combinations of the underlying data, but

this is not usually helpful to understand the resulting

semantic space. Rather the axes should be understood as

meaningful directions in which data vary, but the precise

relationship of this variation to that of the original data is

not helpful.

The number of markers used in each experiment is given

in Table 3. Each marker represents a particular word with a

particular tag; hence, although the deception model uses 86

words, 128 tagged words were counted. Clearly spurious

words were removed, but the quality of parsing did not

make it possible to determine every spurious possibility

(e.g., ‘‘mine’’ as a noun instead of a pronoun). For all

models, any word that occurred in more than one document

was counted.

4.1 Nouns

Two campaigns involving hundreds of speeches obviously

cover a large number of topics and so we expect that the

usage of nouns will be diffuse. However, Fig. 1 shows that

the space of nouns forms a rough triangle. At its left-hand

edge are words associated with the process of campaign-

ing: ‘‘president’’, ‘‘choice’’, ‘‘government’’, ‘‘college’’ and

‘‘class’’. At the top right are words associated with general

issues: ‘‘nation’’, ‘‘life’’, ‘‘state’’, ‘‘country’’. At the bottom

right are words associated with economic issues: ‘‘oil’’,

‘‘businesses’’, ‘‘budget’’, and ‘‘taxes’’.

The variation among speeches mirrors this variation in

the usage of nouns, as shown in Fig. 2 (See Table 2 for the

color coding used throughout these figures). The left-hand

end is primarily associated with Obama’s campaign in

2012, an emphasis on election stops on college campuses

and enthusiastic audience response. The top-right hand

corner represents the focus of content in the 2012 election

for all of the other candidates, and for Clinton in 2008. The

bottom right corner is entirely occupied by speeches from

the 2008 campaign (McCain vs. Obama), where the

economy suddenly became the main focus late in the

campaign (after Clinton had dropped out). It is striking how

little these topics were mentioned in the 2012 campaign.

Figure 3 shows the same figure but with the labelling

simplified to election cycle and party. This shows two

things: first, Obama’s content changed strongly between

the two election cycles (blue stars vs. blue circles). Second,

the Republicans and Democrats talk about different issues

(at least in terms of the nouns they use) with blue domi-

nating slightly in the left of the figure and red in the right.

Figure 4 shows changes in the use of nouns over time

for each candidate, with each placed in the common

semantic space provided in Fig. 1. It thus allows us to see

not only how much variability each candidate exhibits over

time, but also which part(s) of the content space they cover

in their speeches. The scale of the figures is the same so

that direct comparisons can be made.

Notice first that almost every candidate spends their time

along the top edge of the triangle. The exceptions are

Table 2 Symbol coding for results

Politician Symbol

Clinton Magenta star

McCain Red star

Obama (2008) Blue star

Gingrich Green circle

Paul Yellow circle

Romney Red circle

Santorum Black circle

Obama (2012) Blue circle

Table 3 Number of tagged words used for each model

Model Number of markers

Nouns 10,960

Adjectives 2,910

Verbs 5,908

Adverbs 792

Positive 325

Negative 1,205

Deception 128


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McCain and Obama in 2008, where the topics were more

wide-ranging. It is not surprising that candidates tend to

talk about similar topics, since remarks by one may attract

rebuttal by another. However, something more general is at

work, for there is considerable agreement between, say,

Clinton in 2008 and Romney in 2012, showing that there

are common topics of concern over longer periods of time.

Figure 5 shows variation in the use of nouns with time

for all candidates (the y axis of this figure represents the

x axis positions in Fig. 2 arranged by candidate and then by

−0.4 −0.2 0 0.2 0.4 0.6 0.8 1−1.5

−1

−0.5

0

0.5

1

money

crisis

economy

wall

taxes

businesses

dollars

congress

country

street

plan

business

leaders obama

people

jobs

washington

history

week senator

america

help

homes

thing

opportunity

tax

president

times

credit

months

home doors

campaign

opponent

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millions $

republicans

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states growth budget

program democrats

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cuts

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support

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market

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students

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fight investments interests

house

moment

side

regulations vote

days

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party vision clinton

class debt

bill

path

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romney

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trade

issue

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number

education schools

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place things

school freedom folks

percent the

governor

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policies

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$

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cars wind power

system

families

companies gas

insurance cost

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energy costs health

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v1

v2

Fig. 1 Variation among nouns.

The axes of such figures

represent linear combinations of

all of the speeches (resp.

words), and so are not directly

interpretable—but they

represent directions in which

there is greatest variation in

each dataset, and so have an

intrinsic meaning

−1.5 −1 −0.5 0 0.5 1 1.5−1.5

−1

−0.5

0

0.5

1

1.5

u1

u2

Fig. 2 Variation among

speeches based on noun usage


123


time). This provides deeper insight into short-term chan-

ges. Both McCain in 2008 and Obama in 2012 show

considerable flattening towards the end of the respective

campaigns, with lower variation from speech to speech.

Presumably this reflects a well-honed stump speech which

becomes somewhat automatic. Obama also shows a trend

over the entire campaign towards the cluster of nouns that

appear at the left-hand end of Fig. 1.

4.2 Adjectives

Nouns seem to provide little opportunity for differentiation,

but adjectives can potentially create such an opportunity;

they create the possibility of differentiated tones about the

same issues by, e.g., how positive or negative they are

(which we will also explore in more detail).

The range of use of adjectives is shown in Fig. 6. It

exhibits a triangular structure that appears to match that of

nouns, albeit more weakly. The words at the bottom right

are adjectives that naturally associate with the economic

content of the nouns in the corresponding area. The words

at the top right are adjectives that associate with the

national issues of the nouns in the corresponding area,

making sharp distinctions between those aspects that are

going well (‘‘great’’) and those that are not (‘‘hard’’).

The words at the left of the figure are adjectives that dif-

ferentiate different groups: ‘‘international’’, ‘‘homegrown’’,

‘‘black’’, ‘‘universal’’, ‘‘african’’, ‘‘hispanic’’, ‘‘rural’’, ‘‘old’’.

As Fig. 7 shows (and Fig. 8 even more clearly), the

separation is primarily between Democrats who use

adjectives from the left of the spectrum and Republicans

who use adjectives from the right. Both parties are drawn

to the positive adjectives on the upper right as well. It is

also noteworthy that Romney exhibits a wider range of

adjective use than any other candidate.

Figure 9 shows the variation in adjective use with time,

and shows the overall similarities, with only the slight

leftward or rightward bias between parties.

4.3 Verbs

Verbs have received little attention, and yet we might

expect them to be quite revealing of thinking, intent, and

action. Figure 10 shows the variation among verbs. The

extremal, and so most significant, verbs are all short, many

of them auxiliaries. There are few verbs in the past tense,

although those that appear tend to be in the upper right-

hand area.

Figure 11 shows that there are substantial differences

in how verbs are used. Obama’s 2012 campaign occupies

a space that is almost completely separate from that of

other candidates, including his own in 2008. The spee-

ches from the 2008 campaign are almost entirely along

the lower edge; the Republican speeches from 2012

are almost entirely in the upper right-hand direction

(Fig. 12).

−1.5 −1 −0.5 0 0.5 1 1.5−1.5

−1

−0.5

0

0.5

1

1.5

u1

u2


speeches based on noun usage

for party and cycle (blue

Democrats, red Republicans;

asterisks 2008, circle 2012)

(color figure online)


123


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−1

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14 22 7

11 25 16

4 21 19

6

−1.5 −1 −0.5 0 0.5 1 1.5−1.5

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57 50

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55 37 38

3

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68

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63

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13

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4 30

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24

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39 32

25

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31

7

16

−0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6 0.8 1−1.2

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0

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38

31

28

81

22

102 78

104

6 72

14

37

26

41

107

46

50 5 16

63

57

62

47

51

33

71

48

75

4

94

21

1

3

80

27

52

68

56

55

54

69

66

96 74 12

9

32 15 43

64

60

11 24 7

20

34 39

58 30

85 89 82 84 88

95

77

61

45

53

36

65

86 91

83

25

10 2

73

79

90

23 29

100 105

13

97

8

67 87

92 98 93

19

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99

49

42 103 109

113

70

106

101

35

111

40

110 76

18

112

59

17 44

−1.5 −1 −0.5 0 0.5 1 1.5−1.5

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6

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3 5 1 2

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8

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18

41

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23

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72 8

65

60 32 48

5 56 21

85

132

3

688272

134

12 126

152

90 131 128

129 94 130

117 91 136 133

86

20

84 71

6

83

62

118 17

87 116 137

22

63

36

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33 25

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29

106

135 64 121 140 120 61 115 108

59

92 146 150 88 93 112 19

66 101 30 89 124 125 142 34

13 102 143 79 139

46

81

151 16 52 38 73 37 75 76

82

145 69 9

138

111 1 78 141

148 123 113 74

4 144 95 70 67 147 2 31

35

55 10 80 96 77

24

97 103 110 104

51

45 39 58

109 99

127 50

42 100 44 98 149

114

40 11 53 105 43 57

122

47

(a) (b)

(c) (d)

(e) (f)

(g) (h)

Fig. 4 Temporal patterns in the

use of nouns


123


The temporal structure of the use of verbs is some-

what different from that of nouns and adjectives: a

tendency for more looped patterns, and some exam-

ples of large anomalies in verb use for a single speech

(Fig. 13).

Figure 14 shows the changes in verb use with time.

Again McCain in 2008 and Obama in 2012 show a flat-

tening in verb choices towards the end of the campaign.

Obama’s verb use has a similar trajectory in both cam-

paigns; so does McCain’s but in the opposite direction.

0 50 100 150 200 250 300 350 400 450−0.2

−0.15

−0.1

−0.05

0

0.05

0.1

0.15Fig. 5 Time sequence for

variability in noun use over all

candidates. 1–32 Clinton,

33–108 McCain, 109–222

Obama 2008, 223–229

Gingrich, 230–382 Obama

2012, 383–388 Paul, 389–411

Romney, 412–421 Santorum,

color coding as before (color

figure online)

−0.2 0 0.2 0.4 0.6 0.8 1 1.2−2.5

−2

−1.5

−1

−0.5

0

0.5

1

1.5

2

young

solar

new

own

good

clean renewable natural possible serious

old

higher

local

full

white

true worst

environmental efficient

willing

real

green stronger

rich future elderly

easy largest

private

sick major

tough civil confident asian

strongest free such recent

fuel−efficient greater nuclear brave decent global

wrong

certain high rural popular smart social

tougher black proud

safer

terrible average

red extraordinary

federal

whole

wealthy

successful human dark

expensive necessary worse dependent

little

east nation−building common democratic fine massive quick short

cynical secure

international native supreme

south presidential grateful

worth beautiful straight

enormous bankrupt dangerous familiar cold

huge rewarding homegrown

entire

affordable extra poor productive likely

golden dead essential

typical amazing

final

low

public hispanic top

competitive

difficult

particular

honest

open equal individual immediate

ordinary gingrich comprehensive conservative central

bottom−up

fair

negative

effective

close

independent direct reckless

universal african rid political biggest

prosperous incredible

happy general

north foreign

moral

sure

simple

military

available responsible critical hard

bipartisan

national

ready fundamental al strong

safe clear large

outstanding lower fiscal republican

wonderful

perfect

able

vital medical additional powerful

basic

bad bigger

right

early

wealthiest tragic

corporate

big

personal

long

special main

highest

best

greatest

better different

current

important

financial

middle

small

economic

great

american

v1

v2


adjectives


123


4.4 Adverbs

Adverbs provide another channel for differentiation

because they make it possible to talk about the same issues

as other candidates, and even the same actions, but to

distinguish oneself by a different style.

Figure 15 shows the variation in the use of adverbs. The

right-hand end of the dense triangular cluster contains

−1 −0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6 0.8 1−1.5

−1

−0.5

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u1

u2


speeches based on adjective

usage

−1 −0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6 0.8 1−1.5

−1

−0.5

0

0.5

1

1.5

u1

u2


speeches based on adjective

usage by party and cycle


123


−1 −0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6 0.8 1−1.5

−1

(a) (b)

(d)(c)

(e)

(g) (h)

(f)

−0.5

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15 9

29

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27 13 23

12

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30

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20

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4 25 21

6

18 16 19

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64

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66 74 73

41

13

54 23

61 26

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58 68

49 29 60 30

11 44

52 67

48

59

70 69

4

8

32 14

10

39

20 45

22 24 25 63 46

51

34 7 31

16

−1 −0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6 0.8 1−1.5

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104

38 78

41

81

6 5

16

37

102 46

4

14

22 31

72

107 28

21

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94 33

1

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80

69 71

96 54

56

12

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47

66

9

50 64

26

62

68

27

57 3

34

74

51 2 24 7

20 11

15

77 60

39 53 89

55 58

30

82 85

52 43

100 8 105

95

83

79

67 106 84

97

32

61 23

25

88

92

10 98 99 93 108

36

109

49 73 29

65

103 45

86

19

101 113 17

91

111 110

35

59

40 42 70

76

18 87 44

90

112

13

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3 5

6

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4 1

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4

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13

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12

3 5

16

2

8

11

10

20

21 22

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4

3 5

6 7

1

9

8

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1

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49

7

54

41

23

26 72

14

5

15

18

32

8

65 48

21

56

3 6082 72

85

129

130

132 64 90 62

12

133

126

63 134 33

71 68

152

84

83

91

17

59 20

128

66

19

140

6

136

131 94 117 61

36

93

38 46

137

86 75

37 107

73

69 16 81

108 145 125

116 142 150 121 82

80 135 143

89

151

52 67 70

146

22

139 115

45 113 74 92 58 87

112 118 119 144 106 29

102 138

35

39 13

111

51 57

141

123 50

148

77

9 101 4

79

1

55 34

30

25

124

88 78 24

147

42 76

120

53

2 43 104 10

44 31

149

97 40

109

95 11 96

99

110

105

103 100

98 122 127

114

47

Fig. 9 Temporal variation

based on adjectives


123


−0.6 −0.4 −0.2 0 0.2 0.4 0.6 0.8 1−1

−0.5

0

0.5

1

1.5

2

give let

go

make

keep pay

need

said

cut

ask

want

got

create

united

get

come running

going

spend

happen

afford

asking

elected

work

fight

say

help

cut

know

take finish

turn

says

love

choose

wants

are

getting

fighting

raising

win

trying cuts vote

end

tell

talk

spending

believe

coming

become act lead

bring

heard breaks

build

calls

invest

raise reduce

see

hire

look

grow

giving

failed

put change

rebuild

creating hold

moving bless

try

lose

protect

like

promised

called

move

rebuilding

needs

rising

provide

remind

save

having

hear

let’s

start

strengthen

making

growing buy

makes

struggling

takes decide restore

stop

care

goes lost

’

building passed

helping

cutting

face

ensure

eliminate paying begin

doing

happens putting

solve

stand compete

come ve

stay send

means

pass gets

investing

went

find

offer gone run

got

hope

aren’t

ending

am

deserve

understand succeed

gave

talking

fought helped told

mean

stood working

created starting

leave saw tried saying standing

made

taken call

remember

known

started

feel given haven’t

done

comes

created manufacturing

support

built put looking

knew

taking

isn’t

continue

lost

serve

thought worked

use

took

made

meet

is

came

live wasn’t

think

thank

being

seen have

be been

has

were had was

v1

v2

Fig. 10 Variation among verbs

−1.5 −1 −0.5 0 0.5 1 1.5−1

−0.5

0

0.5

1

1.5

2

u1

u2


speeches based on verb usage


123


conventional ‘‘ly’’ adverbs. The left-hand end is primarily

adverbs of quality and time, e.g., ‘‘nearly’’, ‘‘exactly’’,

‘‘later’’, and ‘‘earlier’’. The adverbs in the lower right are

those that are favored by Obama (2012) and Santorum, as

shown in Fig. 16.

Figure 17 shows a standard pattern of adverb use for all

of the candidates in the 2008 cycle and for the Republicans

in the 2012 cycle. Once again, Obama’s language use in the

2012 cycle is very different to all of the others. This may be

partly explained by adverbs such as ‘‘back’’, ‘‘here’’,

‘‘now’’ that may reflect relentless campaigning, but it is

still startling.

Figure 18 shows the variation with time for each of the

candidates. The patterns are qualitatively quite similar for

all of them.

Figure 19 shows the variation in use of adverbs with

time. Again we see a flattening for McCain in 2008 and

Obama in 2012 as they reduce the number of different

patterns of adverbs they use.

4.5 Positive words

We now turn to explicit word lists that describe positivity

and negativity. Both of these lists were developed in a

business context, so they have an economic or consumer

flavor (rather than a directly adversarial flavor).

Figure 20 shows the variation among these positive

words. The basic shape is single-factored with the most

positive words at the left (‘‘win’’ a popular election word,

‘‘strong’’, ‘‘progress’’) and more generic and emotionless

words at the right (‘‘enable’’, ‘‘enhance’’, ‘‘advantageous’’,

‘‘efficient’’). The words ‘‘good’’ and ‘‘great’’ behave dif-

ferently from all of the others, and as antonyms of one

another, perhaps because both are typically almost empty

of content and the choice between them becomes an indi-

vidual habit. The fact that the structure is almost exactly

single-factored shows that this list does capture a property

of the document set that varies in a linear way.

Figure 21 shows the variation among speeches, much

expanded vertically compared to the word variation, but

still essentially single-factored. There is much less struc-

ture to the variation than for any of the word categories we

have seen so far—every candidate shows considerable

variation from high to lower positivity (except perhaps

Santorum).

Figure 22 shows a very weak differentiation by party

with points corresponding to Democratic candidates slight

above those of Republican candidates—almost certainly

because of higher rates of occurrence of ‘‘good’’ rather than

‘‘great’’.

Figure 23 shows more directly that there is considerable

variation in the way that all candidates use these positive

words over time. This is evident even for those candidates

for whom only a small number of speeches are included. It

is evident that Obama’s positivity decreases between the

2008 and 2012 campaigns.

−1.5 −1 −0.5 0 0.5 1 1.5−1

−0.5

0

0.5

1

1.5

2

u1

u2


speeches based on verb usage

by party and cycle


123


−1.5 −1

(a)

(c) (d)

(f)

(h)(g)

(e)

(b)−0.5 0 0.5 1 1.5

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0.5

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3 1

15

9 2

29 23 27

24

26

30

5 10

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28 31

20 7

14

8 21

22

11

18

4 25

16

19

6

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56

72

57

47

55

53

62

3

50

71 65 66 5

61

1 6 73

75

21 74 19

43 67

37

68

18

15 60 64 70 42

40

35 38 69 58

12

17 63

9

28

2

4

52 54

23 29 59 36 30

8

49

46

33 26

10

11

48 41

44 13

25 51

39

45 20 34

32 27 22

24

14

31 7 16

−1.5 −1 −0.5 0 0.5 1 1.5−1

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0

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1

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2

38

22

14

6

81

28 31 102

46 78 16 48

62 33

26 50 104

72 94 41

37 1

51 66

9

107

21

57

54 64 80 12 3

5

63 75 55

71 74 15

96

4

69 58

11 27 24 20

68 60

47 53 30 32

95

2

65

34

7 82

39

43 52 77 85 10

23 89 61 25

56 84

45 83 105

36

88 100

79 29

97 86 99 108 8 98 92

91

113 93

109 106 101 103 73

70

87 111 35

67 110 13

49

40 18 112

42

19 76 59 90

17

44

−1.5 −1 −0.5 0 0.5 1 1.5−1

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0.5

1

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2

1

4 3

5

6

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2

3

1 5

4

2

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14

17

18

4

15 6

16

13

7

8 3 12

1 2

19 10 5 11

21

20 22

−1.5 −1 −0.5 0 0.5 1 1.5−1

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2

2

3

6

4

1 5 7

9

8

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49

7

15 48

14 8 21 65 23

72 18 54

26 60

5 32

56

85 132 3

27 28

130 94 131 90 134

12

152

128

126 133 62

6

119 117

17

121 118 116

91 129 63 68 108

22

61 135

115

71 20 33

136

36

84 92

120

87

107

19

16

124 64 86

46

125

25

112

38

139 137

59 37

13

140

142

83 79 78 66

102

35

143

106 81 89

150 145

9

82

52

146

93

75

29

76

1

73 123 69

101

141

67

151

70

4 10

55

111 30

88

58

34

2 138 147

110

148 144

95

113

42

104

77 45

96 24

74

97

50

99 80

31

51

109

98

103

105 100

43

11 114 39

44 57

149

40 53

127

122 47


based on verbs


123


Figure 24 shows the variation in use of positive

words with time. Clinton shows a decrease as the bit-

terly fought primary campaign draws to a close.

McCain shows a sudden sharp increase late in the 2008

campaign, possibly reflecting the moment when it

appeared that his chances had improved. Romney

shows large oscillation in the later stages of his

campaign.

0 50 100 150 200 250 300 350 400 450−0.2

−0.15

−0.1

−0.05

0

0.05

0.1

0.15Fig. 14 Trend in verb use with

time for all candidates

−2 −1.5 −1 −0.5 0 0.5 1 1.5 2−2.5

−2

−1.5

−1

−0.5

0

0.5

1

even

more

still

well

off

only

then

back

so

better

somehow

instead

ago

ahead

because ever

longer

also

best

rather already over

yet

before

everywhere

often

first alone sometimes importantly simply

— – else

bravely twice elsewhere

overseas soon gladly

obviously

easier " nearly suddenly usually

always

directly

fundamentally

however aggressively

probably completely strongly basically

just

nowhere almost

forward

backwards behind generally seriously effectively

greatly here’s offshore

maybe

mr differently economically long apparently unfortunately further

too

quickly fully wisely

along easy

anywhere

otherwise — meanwhile mostly slowly

fast honestly – — surely

" forth forever currently badly forwards

absolutely

regardless eventually

hard

rally perhaps faster

through

later apart –

away

someday barely overnight anyway

safely exactly responsibly automatically potentially historically according

aside re dramatically consistently illegally backward

desperately definitely necessarily ” clearly easily organizer "

now

s ill "

— constantly yeah entirely straight harder

abroad ’

deeply

literally precisely

close

’

particularly

less frankly ultimately in

politically fairly late

recently . either closer t

immediately somewhere truly

right no

rarely certainly earlier

— –

early upon anymore most

far

low

down

once finally especially

really

around

much

together

on

there

about

sure

actually

yes

never

here

again

out

up

v1

v2


adverbs


123


4.6 Negative words

The variation among negative words is shown in Fig. 25.

Once again it is almost a single-factored structure,

validating it as a word list that genuinely captures an

underlying property. The exceptional words (‘‘crisis’’,

‘‘cut’’, ‘‘deficit’’) are all words that are particularly ger-

mane to political discussion and they are evidently used in

−1.2 −1 −0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6 0.8−1.2

−1

−0.8

−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

u1

u2


speeches based on adverb usage

−1.2 −1 −0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6 0.8−1.2

−1

−0.8

−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

u1

u2


speeches based on adverb usage

by party and cycle


123


−1.5 −1 −0.5 0 0.5 1−1.2

−1

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0

0.2

0.4

0.6

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18

19

4 7

16

6

28

11

14 22

25

20 12

21

17

8

31

26 30 10

29 27

5 13

23

24

2

15

1

9

3

(a) (b)

(d)(c)

(e) (f)

(h)(g)

−1.5 −1 −0.5 0 0.5 1−1.2

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56

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44

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32

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18

26

38 60 61

22

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33

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37

30 28

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74 35

21

68

63 72 42 5

67

64

70 73

36

19

13

69

8

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1 6

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57

66 43

71

40

65

3

62 55

12

50

−1.5 −1 −0.5 0 0.5 1−1.2

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44

70

13

59

87

42 67

19

8 112

90 113

108

106 61

100

86

76

101

35

109

25 111

93

91

110

103

23

92

29

98

45

17 40

105 83 88

89

84 58

73 97

99

27

36

79

77

32

47 71 74

56 39 95

85 82 60

102

10

66 68

64 80 63

78

20 12

30

7

65

24 33

43

75

52

94 69

34

72

81

49

2 11 50 3 51

57

15 16

41

26

62

55

5 46

104

53

6

21

96

1

48

22

37

54 4 31 9

107

14

38

28

−1.5 −1 −0.5 0 0.5 1−1.2

−1

−0.8

−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

6

3

5

4

1

2

−1.5 −1 −0.5 0 0.5 1−1.2

−1

−0.8

−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

4 2 5

1

3

−1.5 −1 −0.5 0 0.5 1−1.2

−1

−0.8

−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

20

22

21

11 5

19

10

15

1

12

8 18

3

6

16 13

14 17

7 2

9

4

−1.5 −1 −0.5 0 0.5 1−1.2

−1

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−0.4

−0.2

0

0.2

0.4

0.6

0.8

8

1

9

7

6

5

2

4 3

−1.5 −1 −0.5 0 0.5 1−1.2

−1

−0.8

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−0.4

−0.2

0

0.2

0.4

0.6

0.8

47

50

74

78

57

77 40

105

114

43

103

80

100

122

53 69 58 104 98

99 67

36

127

35

110

70

148

76 121 44 102

75

113

39

55 79

111

42

2

52 141

1

24 10 109

82 38 124

46

34

30 120

9

125

97

73

112

95

81

29

144

4

45 96

142

11

149

51 25

17

89

31

33

101

93

140

13

66

59

147

37

128

63

137 138

61

107

151

117

115 92 129

16

139

64

83 145

123 22

116

71

126

135

119

86 143

68

150

91

136

106

6

108

118

88 94 84

132 12

87

19

20

133

134

131

146 90

82 72

48

62

130

23 65

5

85

60

54

56

8 21

152

26

49 18 32

14

15 7 3

72

41


based on adverbs


123


a different way than the remainder of the words—perhaps

they are not really regarded as negative in this context.

Examples of words at the right-hand end are ‘‘against’’,

‘‘worst’’, ‘‘bad’’, ‘‘problems’’, ‘‘lost’’, and ‘‘serious’’.

Words at the left-hand end are more specific and again less

emotionally charged: ‘‘criminals’’, ‘‘doubted’’, ‘‘obsolete’’,

‘‘disregards’’, ‘‘contempt’’, and ‘‘secrecy’’.

Figure 26 shows the variation among speeches, with

negativity increasing to the right. Again there is little dif-

ferentiation between candidates, except that Obama’s 2008

0 50 100 150 200 250 300 350 400 450−0.15

−0.1

−0.05

0

0.05

0.1

0.15

0.2Fig. 19 Trend in adverbs with

time for all candidates

−2.5 −2 −1.5 −1 −0.5 0 0.5−2

−1

0

1

2

3

4

better−JJR

opportunity−NN

prosperity−NN dream−NN

strong−JJ

win−VB opportunities−NNS improve−VB progress−NN easy−JJ perfect−JJ stronger−JJR success−NN strongest−JJT

innovation−NN ingenuity−NN dream−VB

despite−IN benefit−VB

prosperous−JJ rewarded−VBN rewarding−JJ

outstanding−JJ

benefit−NN strengthens−VBZ happiness−NN

strengthen−VB

efficient−JJ advantage−NN

enjoy−VB reward−VB winning−VBG beautiful−JJ innovative−NN

confident−JJ honor−VB succeeding−VBG

greatest−JJT

easier−RBR easy−RB resolve−NN resolve−VB advancing−VBG

achieve−VB

favorite−JJ efficiency−NN advantages−NNS gain−VB happy−JJ stabilized−VBN ideal−NN encouraging−VBG advances−NNS creativity−NN succeeded−VBN efficiently−RB invented−VBD optimistic−JJ

gain−NN boom−NN profitable−JJ alliance−NN alliances−NNS encouraged−VBN destined−VBN exciting−JJ

strength−NN

invent−VB stabilize−VB greater−JJR achieving−VBG prospers−VBZ enjoyed−VBD enhancing−VBG enhance−VB excellent−JJ successful−JJ achievements−NNS solving−VBG incredibly−QL benefiting−VBN enjoyed−VBN easier−JJR smooth−JJ reward−JJ accomplished−VBN exceptional−JJ encourages−VBZ innovates−NNS honors−NNS assures−VBZ innovating−NN inventing−VBG popular−JJ excitement−NN effective−JJ benefiting−NN pleased−VBN superior−JJ assured−VBD excellence−NN loyal−JJ distinction−NN honoring−VBG breakthroughs−NNS accomplished−VBD friendly−JJ vibrant−JJ honorable−JJ adequately−RB perfected−VBN spectacularly−RB innovator−NN inventors−NNS exclusively−RB collaborative−NN rebound−NN collaborating−NN enables−VBZ encouraging−JJ desired−VBN prospered−VBN benefited−VBN improves−VBZ accomplishments−NNS upturn−NN winner−NN assured−VBN inventions−NNS outperforming−VBG empower−JJR enjoys−VBZ favoring−VBG efficient−NN collaborate−VB invention−NN encouraged−VBD empowering−VBG breakthrough−NN accomplishment−NN enjoying−VBG lucrative−JJ able−VB profitability−NN tremendously−QL creative−JJ encouragement−NN good−UH benefitted−VBN attain−VB dependable−JJ achievement−NN enable−VB enabled−VBN proactive−JJ succeed−VB inventive−JJ boosted−VBD strong−RB beneficially−RB regained−VBN boom−UH benefiting−VB exceptionally−QL attainment−NN exclusive−JJ inspirational−JJ innovating−VB progresses−VBZ good−RB vibrancy−NN diligent−JJ satisfying−VBG win−NIL delightful−JJ improved−VBD enthusiastically−RB happiest−JJT satisfying−JJ good−NP impressed−VBD surpassed−VBN compliment−NN regained−VBD regain−RB meritorious−JJ rebound−VBN revolutionize−NNS prospering−VBG achieves−VBZ distinctive−JJ compliment−VBN reward−NP collaborated−VBD desirable−JJ solves−VBZ unsurpassed−JJ bolstered−VBN beautifully−RB accomplishes−NNS rebound−VB outperformed−VBD honored−VBD perfect−VB exemplary−NN beneficially−NN favorable−JJ satisfactory−JJ perfectly−RB rebounded−VBN benefiting−JJ accomplishing−VBG winner−NP creatively−RB favorites−NNS stabilizes−VBZ improved−VBN gained−VBD innovate−VB great−QL pleased−VBD enhances−VBZ boost−VB advantageous−JJ constructive−JJ beneficial−JJ enabled−VBD delight−NN inspiration−NN progress−VB spectacular−JJ surpassing−VBG enhanced−VBN stabilization−NN empower−VB win−NP excited−VBN gain−RB assuring−VBG booming−VBG stable−NN invented−VBN attractive−JJ advancement−NN winners−NNS stabilizing−VBG prospered−VBD plentiful−JJ satisfied−VBN regain−VB win−NN gained−VBN ideal−JJ innovators−NNS empowered−VBN distinctions−NNS incredibly−RB regaining−VBG abundant−JJ succeeded−VBD honors−VBZ charitable−JJ brilliant−JJ valuable−JJ pleasant−JJ stabilized−JJ boost−NN improvement−NN strengths−NNS innovations−NNS collaboration−NN diligently−RB popularity−NN happily−RB strengthened−VBN influential−JJ positive−JJ favored−VBN successfully−RB honor−NN

prestige−NN achieved−VBN impressed−VBN impress−VB accomplish−VB receptive−JJ satisfaction−NN leading−VBG worthy−JJ

honor−NP stability−NN strengthening−VBG achieved−VBD perfectly−QL gaining−VBG

incredible−JJ enthusiastic−JJ honored−VBN

fantastic−JJ improvements−NNS stable−JJ transparency−NN successes−NNS improving−VBG delighted−VBN rewards−NNS

enthusiasm−NN good−NN

leadership−NN

tremendous−JJ integrity−NN impressive−JJ pleasure−NN greatly−RB reward−NN succeeds−VBZ easily−RB gains−NNS highest−JJT

greatness−NN assure−VB

better−RBR able−JJ

good−JJ

great−JJ

v1

v2


positive words


123


speeches tend to be towards the top and his 2012 speeches

towards the bottom, probably reflecting the importance of

the global financial ‘crisis’ in 2008 (Fig. 27).

Notice that it is possible to be both more positive and

more negative than average, e.g., Santorum. Thus, posi-

tivity and negativity, measured this way, are not two ends

−0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6−0.8

−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

u1

u2


speeches based on positive word

usage—increasing positivity to

the left

−0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

u1

u2


speeches based on positive word

usage by party and cycle


123


−0.8 −0.6

(a)

(c)

(e) (f)

(h)(g)

(d)

(b)−0.4 −0.2 0 0.2 0.4 0.6

−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

16 6

25

7

22

13 14

21

4

18

11 27

29 19

17

12

30

20 28

10 26

23

24

2

31

1

8

5 9

15

3

−0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6−0.6

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0

0.2

0.4

0.6

0.8

24

25 7

44 46

11

30

16 14

20

18

39

58

10

27

32

5

4 9

2

1

33

15

51 40

36

49 34

52

13

29

45

3

37

54

42

38

23

12

41

43

48 8

21

26

56

19

31

59

6

22

67

69

63 35

28

60

17

64

50

57

53

74 47 73

61 75

68

66

72

65 71

70

62

55

−0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

19

59

44

76

18

40 35

73

13

87 112 110 111

70

86 52

17

39

67

77

92 82

45

90

57

42

88

29

83 49

79

104

61

36

7

10

43 93

89

68

109

64

108 85 95

65 113

98 8

33

99

84

80

66

25

106

30 11

97

100

60

103

75

50

20

26

101

55

102

58 62

53

28

81

78

32

23

54 24

105

69 91

14

12

71

4

96

27

9

63 3 37

47

107

34

74 16

22

94

41

56

5

21 6 72

46

31

15

51

2

38

48

1

−0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

6

5

3

2

4

1

−0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

1 2

5

3

4

−0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

19

22

5

1 21 20

11

10

2

15

8 13

3

6 12

16

14

7

9

4

18

17

−0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

8

7

1 4

9

5

3

2

6

−0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

31 11

57

100

110 122 70

88

2

55

19 95 47

112

113

39

101

53

99

103

1

111

12

34

98

137 44

83

36 51

45 50

29

138 127

109

89

42

59

25 136

30 96

4

40

106

139 115

87

33

22

92

17

105

10

9 37 97 66

143

16

116

13

140

43

141

84

114 24

149

6

80

108

102

77

118

58

107

117

94

147

151

64

81

71

69

76

148

142 145

56

82

20

144

82 72

35

90

86

104

125

54

5

120 46

75

123

63

3

67

85

91

73 79

26

146

8

78

23

60

7

52 152 38

128 74

126

119

14

32

121

93

131

129

15

61

132

150 135

72

124

21 62

68

130

18

133

48

134

49

65

41

Fig. 23 Variation based on

positive words over time


123


of a spectrum but two different (and, to be sure, somewhat

opposed) spectra.

Figure 28 shows that variation of negative language use

with time. Notice that all candidates show considerable vari-

ation, even those for whom few speeches have been collected.

Figure 29 shows the variation in negative words with

time. For all candidates, the main pattern seems to be that

negativity increases in brief (4–10 speech) bursts, and then

reverts to a more typical level. There is a slow decrease for

Obama over time.

0 50 100 150 200 250 300 350 400 450−0.2

−0.15

−0.1

−0.05

0

0.05

0.1

0.15Fig. 24 Trend in positive

words with time for all

candidates

−0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.4−3

−2

−1

0

1

2

3

4

bad−JJ lose−VB

deficits−NNS question−NN

difficult−JJ unemployment−NN lost−VBD broken−VBN

disaster−NN

worst−JJT challenge−NN doubt−NN

dangerous−JJ disagree−VB

critical−JJ

threats−NNS sacrifice−VB

failure−NN adversity−NN

violate−VB fear−NN

defeat−NN worse−JJR petty−JJ

violence−NN fraud−NN

opposed−VBD defend−VB

denied−VBN hurting−VBG threaten−VB barriers−NNS abolish−VB defeat−VB confront−VB crucial−JJ tragedy−NN

questions−NNS

disappointed−VBN danger−NN

refinance−VB reckless−JJ recall−VB destruction−NN unacceptable−JJ overcome−VB breaks−NNS force−VB threatened−VBN corruption−NN troubles−NNS illegally−RB dissent−NN hardship−NN sacrificed−VBN lost−VBN fears−NNS

argument−NN

urgent−JJ stopped−VBN failed−VBD

closed−VBN complicated−VBN refinancing−VBG absence−NN wasted−VBN foreclosures−NNS

refusing−VBG prevents−VBZ overlooked−VBN diminished−VBN obstacle−NN bridge−NN concern−NN late−JJ reject−VB penalties−NNS moratorium−NN concerned−VBN distract−VB serious−JJ

hardships−NNS suffer−VB strain−NN deprived−VBN inevitable−JJ catastrophe−NN accident−NN delayed−VBN deeper−RBR fails−VBZ disappearing−VBG bankruptcies−NN overcoming−VBG broken−JJ burdens−NNS foreclose−VB concerns−VBZ losses−NNS deepest−JJT casualties−NNS arguing−VBG drag−VB complain−VB obstacles−NNS dangers−NNS missed−VBN undisclosed−JJ damage−NN contrary−JJ confused−VBN defaults−NNS vulnerable−JJ seriously−RB weakened−VBD arrest−NN fear−VB frustrating−VBG sacrificing−VBG prevention−NN disappear−VB defeats−VBZ preventing−VBG

easing−VBG delay−NN weakening−NN careless−JJ defeating−VBG abusive−JJ dysfunctional−JJ investigate−VB ill−RB deny−VB defending−VBG ignore−VB closed−VBD opposed−VBN monopoly−NN forced−VBN accused−VBN bail−NN suffered−VBN collapsing−VBG catastrophic−JJ misunderstood−VBN drastic−JJ provoke−VB distressed−VBN criticize−VB tolerate−VB conflict−NN doubt−VB erodes−NNS counterfeit−JJ concede−VB disadvantaged−JJ risky−JJ convictions−NNS error−NN collapsed−VBD argue−VB challenging−JJ protests−NNS burdensome−JJ immoral−JJ overpayments−NN defended−VBN impaired−VBN unstable−JJ slowdown−NN bailout−NN loses−VBZ distorting−NN disregard−NN claims−NNS confined−VBN burden−VB destroyed−VBN damaged−VBN unreasonable−JJ alienated−VBN disregards−VBZ

challenges−VBZ summons−NN limitations−NNS weaker−JJR injuries−NNS panic−NN misplaced−VBN delay−VB persistence−NN sue−VB manipulation−NN bad−VBD criminal−NN insufficient−JJ slower−JJR drastically−RB abandonment−NN halt−VB overcome−VBN contrary−NN seized−VBN disrupted−VBN disproportionately−RB foreclosed−VBN shortfalls−NNS problems−NNS volatile−JJ vulnerability−NN unintended−JJ questioned−VBN scrutiny−NN calamitous−JJ persist−VB shortage−NN barrier−NN sharply−RB reluctant−JJ breakdown−NN misled−VBD protested−VBD poorly−RB defer−VB ignoring−VBG prosecution−NN severity−NN faults−NNS illegal−JJ offended−VBN wasted−VBD frustrates−VBZ inability−NN deepening−NN incarceration−NN bankrupt−NN harsher−JJR difficulty−NN collapsed−VBN disagreed−VBD trouble−VB slowed−VBN defended−VBD wrongly−RB unconscionable−JJ unpredictable−JJ tightening−VBG detain−VB violated−VBD prejudices−NNS restructured−VBN pressing−JJ criticism−NN contraction−NN obsolete−JJ exploits−NNS prone−JJ staggering−JJ confronting−VBG challenging−VBG argued−VBD recalling−VBG disappearance−NN disgraceful−JJ fines−NNS criticized−VBD exposed−VBN flawed−JJ collapse−VB delays−NNS defend−NN unfunded−VBN dishonor−VB inconsistency−NN litigate−VB plaintiff−NN suing−VBG idle−JJ lie−NN strained−VBN worry−VB destabilizing−VBG disagreements−NNS complaints−NNS exploiting−VBG difficulties−NNS deficient−JJ sued−VBD foreclosing−VBG defends−VBZ concedes−VBZ deteriorating−VBG recalled−VBN seriousness−NN misunderstanding−NN distortion−NN eroded−VBN degrading−VBG suspected−VBN disputes−NNS confinement−NN seizing−VBG disappears−VBZ penalize−VB disasters−NNS incompetent−JJ prosecuted−VBN refused−VBN inflicted−VBN ignores−VBZ quit−VB disagreed−VBN destabilize−VB embarrass−NN disregarded−VBN abolishing−VBG distracted−VBN disgrace−NN distressed−JJ harm−NN depressing−JJ rejecting−VBG uncontrolled−JJ exploit−VB argued−VBN coercion−NN offend−VB obscene−JJ contempt−NN prejudice−NN injurious−JJ unaware−JJ criticizing−VBG controversial−JJ omit−VB discourages−VBZ guilty−JJ condemns−VBZ threatening−VBG miss−VB impediment−NN protest−NN stops−VBZ disadvantage−NN mistakes−NNS liquidate−NN intimidation−NN erode−VB deliberate−JJ unfortunately−RB diminish−VB stagnation−NN strains−NNS weakest−JJT deceptive−JJ underinsured−VBN unpaid−JJ picketed−VBD casualty−NN incomplete−JJ declining−VBG secrecy−NN punished−VBN suffered−VBD failings−NNS fined−VBN misunderstand−VB declined−VBD convicted−VBN contradict−VB exploitation−NN overrun−VBN shutting−VBG offended−VBD conflicts−NNS neglected−VBN bad−RB

foreclosure−NN drag−NN denial−NN disappeared−VBD postpone−VB default−NN fraudulent−NN evade−VB suffering−NN unfairly−RB subjecting−JJ upset−VBN cancel−VB sued−VBN dismissed−VBD weaknesses−NNS lagging−VBG overlook−VB inexperienced−JJ layoffs−NNS decline−NN seized−VBD implicated−VBN vetoed−VBD harmed−VBN faulty−JJ deter−VB abandoned−VBD underfunded−JJ lost−RBT

recession−NN frustrating−JJ drought−NN misrepresenting−VBG accidentally−RB lacking−VBG picket−NN discouraging−JJ turbulence−NN prosecute−VB calamity−NN deepens−VBZ denies−VBZ neglect−NN suspended−VBN miscalculation−NN verdict−NN uninsured−VBN confrontation−NN interrupt−VB errors−NNS posing−VBG slowing−VBG breached−VBN disregard−VB unrest−NN embarrassed−VBN deepened−VBD predatory−JJ denigrate−VB dissenters−NNS tainted−VBN imperative−JJ inefficient−JJ dismissed−VBN dismissing−VBG unfortunate−JJ confine−VB complaining−VBG devalue−VB rejected−VBN suffers−VBZ doubts−NNS depressed−VBN renounce−VB prematurely−RB unexpected−JJ deficiencies−NNS flaws−NNS disturb−VB displaced−VBN surrender−NN interrupted−VBD violation−NN downturn−NN inconsistent−JJ pervasive−JJ inattention−NN hampering−VBG abdication−NN lie−NP cautioned−VBD manipulates−NNS impair−VB defendant−NN imperfection−NN aggravates−VBZ contested−VBN criticizes−VBZ liquidated−VBN missteps−NN bankrupting−NN confessed−VBN problematic−JJ condemned−VBD unproductive−JJ indicted−VBN provoked−VBD inquiry−NN discontinue−VB abdicating−VBG construe−VB unwillingness−NN unsuccessful−JJ ceasing−VBG hinder−NN deceased−JJ hazards−NNS dismal−JJ uncontrollable−JJ surrendering−VBG liquidation−NN overlooking−VBG interrupted−VBN allege−VB divorce−VB imbalance−NN deepened−VBN neglects−VBZ unfriendly−JJ impending−VBG resignation−NN overturned−VBD fatalities−NNS underperforming−VBG embarrassment−NN prejudiced−VBN persisting−VBG unreasonably−QL diminishes−VBZ disavow−VB alienating−JJ refinanced−VBN shut−VBD confrontational−NN stresses−NNS negligent−JJ abrupt−JJ objection−NN devolved−VBN flaw−NN deceitful−JJ lapse−NN diversion−NN pervasiveness−NN carelessness−NN mislead−VB stolen−VBN incidence−NN unwelcome−JJ scandals−NNS shutdowns−NNS drawbacks−NNS insubordination−NN frivolous−JJ provoked−VBN violators−NNS worsening−VBG cumbersome−JJ foregoing−VBG purporting−VBG disproportionate−JJ disparity−NN misses−VBZ encroach−VB slowed−VBD imprudent−RB acquiesce−VB complications−NNS distracted−VBD disturbed−VBN deceit−NN divest−VB prolonged−VBN drawbacks−NN abusing−VBG testify−VB abrogate−VB adverse−JJ terminated−VBN stressed−VBN unsuited−JJ unlawful−JJ laundering−VBG annoyance−NN defaming−VBG terminating−VBG overturned−VBN coerce−VB knowingly−RB wrong−NP stress−VB condemnations−NN critically−QL closing−NN balked−VBD harassment−NN unexpectedly−RB inaccessible−JJ contradictions−NNS bankrupting−JJ imprisonment−NN inaccurate−JJ displace−VB summons−VBZ falsely−RB inadequacy−NN depriving−VBG barred−VBD damage−VB distortions−NNS concealing−VBG diminishing−VBG exoneration−NN harming−VBG interruption−NN interference−NN evading−VBG obscenity−NN protesting−VBG exposed−VBD onerous−JJ distorts−VBZ lost−AP reassigned−VBN disparage−NN construed−VBD penalized−VBN disrupt−VB dissident−JJ disagree−NN defame−VB dissatisfaction−NN insufficiently−RB disqualification−NN bans−VBZ egregiously−QL unavoidable−JJ unsuccessfully−RB worsens−VBZ misses−NNS accusing−VBG harmed−VBD devastate−VB contentious−JJ hinder−VB intermittent−JJ violated−VBN rationalizing−VBG perjury−NN inferior−JJ incorrect−VB boycotting−NN undue−JJ prosecutions−NNS aggravated−VBN protesters−NPS counterfeiting−JJ disincentives−NNS harshness−NN suffer−NN unauthorized−JJ misrepresented−VBN harm−JJ egregious−QL poorly−QL fines−VBZ deterioration−NN unneeded−JJ unlawfully−JJ disqualifications−NNS neglect−VB imbalances−NNS annoyed−VBN resigned−VBN disturbance−NN lose−JJ unsafe−JJ dereliction−NN underestimated−VBN degrade−NN verdicts−NNS interfered−VBN insolvent−NN infraction−NN postponed−VBN defrauded−VB bans−NNS conflicting−VBG distracting−VBG incidents−NNS exaggerate−VB disclosed−VBN endangered−JJ expulsion−NN encroaches−VBZ dissatisfied−VBN diverting−VBG indictment−NN deceptions−NNS disappointing−JJ infractions−NNS shutdown−NN impediments−NNS improprieties−NNS harshest−JJT harassed−VBN canceled−VBN depresses−NNS boycotts−NN concealed−VBN confuses−VBZ harms−VBZ attrition−NN overcharges−NNS repudiate−VB sentencing−VBG recessions−NNS punishments−NNS stagnate−NN objected−VBN misapplied−VBN divest−NN undercuts−VBZ inappropriate−JJ deteriorated−VBN violently−RB sue−NP pleaded−VBD escalate−NN derogatory−JJ suspected−VBD closings−NNS unforeseen−JJ controversies−NNS disagreeable−JJ corrections−NNS indict−VB deadlock−NN underfunded−VBN prosecuting−VBG assaults−VBZ defends−NNS uncompetitive−JJ bankrupts−NN disappoint−VB harsh−JJ grievances−NNS deteriorate−VB anomaly−NN restructure−NN impede−VB erred−VBN stagnating−VBG stagnated−JJ bankrupted−JJ impede−VBD disinterested−VBN damages−VBZ contradicting−VB inequity−NN declines−VBZ questioned−VBD harming−JJ disastrously−RB corrupting−VBG neglecting−VBG accusation−NN erode−VBD punishing−VBG protesters−NNS infringing−NN misjudgment−NN detriment−NN crises−VBZ offender−NN litigant−NN unintentionally−RB intrusion−NN unlawfully−QL hindrance−NN reluctance−NN fail−NN worsen−VB abandons−VBD suspending−VBG panics−NNS detract−VB distorts−NNS refinancing−NN censure−NN stagnated−VBN confronted−VBD dishonorable−JJ renouncing−VBG boycott−VB confiscate−VB summoning−VBG forestalls−VBZ suspended−VBD shortfall−NN worsened−VBN tense−JJ exposes−VBZ counterfeiting−VBG escalating−NN deprive−VB rejection−NN misdirected−VBN allegations−NNS restate−NN impermissible−JJ warn−VB encroachment−NN defeats−NNS degrade−VB punishment−NN fears−VBZ delaying−VBG harassing−VBG fugitives−NNS conceded−VBN incident−NN collision−NN lacked−VBN declines−NNS ill−MD bribery−NN disrupting−VBG disloyal−JJ adversarial−NN divert−VB usurp−VB uncorrected−VBN worse−NN weakens−VBZ offends−VBZ devalued−VBN negatives−NNS lag−VB depresses−VBZ destabilizing−JJ exacerbating−NN forego−VB dissidents−NNS insolvency−NN hostility−NN overcharging−VBG obstruction−NN exaggerated−VBN suspend−VB adversary−NN persistent−JJ breach−NN condemned−VBN fired−VBD immature−JJ worries−VBZ diverted−VBN undermines−VBZ delays−VBZ traumatic−JJ abandoning−VBG grossly−RB opposing−VBG warned−VBN poses−VBZ impedes−VBZ deprives−VBZ endangers−NNS solvency−NN plea−NN forbid−VB burned−VBN relinquish−VB condemning−VBG perils−NNS inconvenience−NN disregarded−VBD disappoints−NNS ill−JJ quit−NN offenders−NNS dangerously−RB worrying−VBG unqualified−JJ distracts−VBZ boycott−NN wrongdoing−NN confessed−VBD punishes−VBZ dispute−NN untenable−JJ demise−NN shocked−VBN injury−NN refused−VBD worries−NNS precipitous−JJ questionable−JJ underpaid−JJ interfere−VB straining−VBG uncover−VB distorting−VBG persisted−VBD tragedies−NNS harm−VB destructive−JJ contend−VB divestment−NN undermining−VBG bail−VB illicit−JJ renegotiating−VBG conceded−VBD fallout−NN disagreement−NN lack−VB condemnation−NN exaggeration−NN ridicule−VB dropped−VBD lingering−VBG threatens−VBZ hostile−JJ manipulating−VBG restructuring−VBG mislead−JJ embarrassing−VBG shortages−NNS substandard−JJ unavailable−JJ discourage−VB unjust−JJ condemn−VB doubted−VBD weak−JJ erratic−JJ surrender−VB damaged−VBD manipulate−VB collapses−VBZ repudiated−VBN warning−NN controversy−NN violating−VBG ignored−VBN

arguments−NNS premature−JJ penalty−NN abuses−NNS destroys−NNS arrested−VBN stress−NN confusion−NN recklessly−RB assaults−NNS incompetence−NN unfunded−JJ claims−VBZ abuse−VB caution−NN confronts−VBZ expose−VB correction−NN suspicion−NN undermine−VB weaken−VB destroy−VB detrimental−JJ imperil−VB defaulting−NN unfair−JJ weakened−VBN restructure−VB deter−NN overturn−VB devastated−VBN defeated−VBN inequities−NNS defensive−JJ degradation−NN defeated−VBD doubtful−JJ accuse−VB confusing−VBG worthless−JJ erosion−NN criticized−VBN slow−VB contradiction−NN unrealistic−JJ incompetents−NNS dishonest−JJ cease−VB shuts−VBZ violations−NNS abuse−NN recalled−VBD criticisms−NNS challenged−VBN disparities−NNS challenged−VBD ineffective−JJ protest−VB distorted−VBN critically−RB setbacks−NNS sacrifices−NNS inadequate−JJ misinformation−NN complaint−NN shut−VB warning−VBG excessive−JJ deliberately−RB subjected−VBN imperfections−NNS cutbacks−NNS slow−JJ criminals−NNS harshly−RB crises−NNS failing−VBG volatility−NN refusal−NN offending−VBG assault−NN suspension−NN bridge−VB accusations−NNS denied−VBD confines−NNS undercut−NN incapable−JJ forced−VBD lack−NN hurt−VBN lie−VB confuse−VB embargo−NN recklessness−NN abused−VBN costly−JJ persists−VBZ claiming−VBG suffering−VBG distractions−NNS objections−NNS instability−NN arrest−VB investigation−NN injured−VBN deterrent−NN burdened−VBN deception−NN frustrations−NNS renegotiate−VB decline−VB loss−NN concerns−NNS exploited−VBN halt−NN disruption−NN corrupted−VBN warnings−NNS conviction−NN confess−VB disclose−VB abandoned−VBN unsustainable−JJ ignored−VBD outmoded−JJ devastation−NN forcing−VBG dysfunction−NN closure−NN opposes−VBZ overdue−JJ impeding−VBG rejected−VBD jeopardize−VB suffers−NNS impossible−JJ concern−VB abandon−VB

burdening−VBG flawed−VBN deterred−VBN distraction−NN endanger−VB overburdened−VBN disturbing−JJ bankruptcy−NN violent−JJ artificially−RB inefficiency−NN aftermath−NN droughts−NNS bankrupt−VB unwilling−JJ mismanagement−NN adversaries−NNS question−VB stagnant−JJ stopped−VBD stops−NNS confronted−VBN disappointment−NN tragically−RB eroding−VBG distort−VB opposition−NN endangered−VBN exaggerating−VBG hurt−VB sluggish−JJ

oppose−VB questioning−NN investigating−VBG harmful−JJ firing−VBG lying−VBG false−JJ pressing−VBG distress−NN destroying−VBG wasteful−JJ shut−VBN dismiss−VB divorced−VBN trouble−NN severely−RB stopping−VBG wasting−VBG disappointments−NNS dropped−VBN disastrous−JJ devastating−VBG disappeared−VBN investigated−VBN troubled−VBN breaking−VBG closing−VBG disagrees−VBZ

mistaken−VBN hurt−NN criminal−JJ failures−NNS losing−VBG damaging−VBG unnecessary−JJ lacked−VBD crime−NN weakening−VBG urgency−NN weakness−NN threatened−VBD

cut−VBD unemployed−JJ severe−JJ peril−NN denying−VBG

deeper−JJR seize−VB challenge−VB undermined−VBN undocumented−VBN negative−JJ late−RB warned−VBD unable−JJ missed−VBD

unpopular−JJ crimes−NNS break−NN suspect−VB fired−VBN frustration−NN slowly−RB misleading−VBG barred−VBN discredited−VBN threat−NN victims−NNS

frustrated−VBN inconvenient−JJ discouraged−VBN break−VB turmoil−NN refuses−VBZ mistake−NN corrupt−JJ

slowest−JJT

force−NN sacrifice−NN inaction−NN wrong−JJ fault−NN

bankrupt−JJ burden−NN outdated−VBN

against−IN collapse−NN failed−VBN

challenges−NNS problem−NN

tragic−JJ fail−VB

cut−NN

poor−JJ

refuse−VB

cut−VB

breaks−VBZ cut−VBN deficit−NN

crisis−NN

v1

v2


negative words


123


4.7 Persona deception

Although the media tends to fixate on factual deception by

politicians, manifest in a plethora of fact checking, there is

little evidence that voters care much about it (Druckman

et al. 2009). This may be because voters have been trained

that politicians’ factual statements are unattached to reality,

and so do not serve as discriminators among them. But it

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word usage—increasing

negativity to the right

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speeches based on negative

word usage by party and cycle


123


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Fig. 28 Variation in negative

words over time


123


may also be that, given a limited amount of attention,

voters make up their minds based on perceived personality.

If this latter, then trying to appear better, more compe-

tent, and more attractive as a candidate is a necessary

strategy.

The effort to present a persona that is not one’s actual

personality appears to cause the same textual changes that

occur when factual deception is being employed. We can,

therefore, use the Pennebaker model to assess the extent to

which candidates are trying to present a facade that differs

from reality. This need not be conceived of as a negative

process—all of us attempt to come across as better than we

perhaps are in social situations. Campaigning is just this

process writ large.

Figure 30 shows the variations among the words of the

deception model. The words far from the origin are those

that show the most variation across speeches—it is entirely

typical that these are ‘‘I’’ and its contractions, ‘‘but’’ and

‘‘or’’ as exclusive words, and ‘‘go’’ and ‘‘going’’ as action

verbs. Because of the reversal of direction applied to first-

person singular pronouns and exclusive words, the points

corresponding to them represent reduced frequencies of

their occurrences.

Figure 31 shows the variation among speeches. The

property of deception is two-factored, one factor primarily

associated with first-person singular pronoun use, and the

other primarily with exclusive word use. These tend to be

uncorrelated in normal use, and this is, therefore, reflected

in the changes caused by deception. The figure contains an

axis which runs from maximal deception values (the red

end) to minimal deception values (the green end).

Figure 32 shows that the highest levels of persona decep-

tion are those of Paul and Santorum, both making an attempt

for a job that is a huge stretch for either and, therefore,

needing to project a persona far beyond any they have used

previously; and to a lesser extent Obama in 2008, who faced a

similar challenge. In contrast, Clinton exhibits very low

levels of persona deception, in part because she drops very

easily into exclusive word use in policy-heavy speeches, and

because she made very personal appeals to a very well defined

constituency, resulting in high rates of first-person singular

pronouns. Again there is a sharp distinction between the

model words used by Obama in 2008 and 2012, but the levels

of persona deception remain roughly the same.

The differences among candidates are even more visible

in the language patterns over time, which exhibit more

variation among candidates than any we have shown.

Figure 33 shows the changes in persona deception with

time. The values on the y axis are the sums of the values on

the first two axes in the projection shown in Fig. 31. Two

things are striking in this figure: the amount of short-range

variability (from day to day), and the amount of medium-

range variability (from week to week). This seems to be

evidence that it is difficult to maintain a particular level of

persona deception or, to say it another way, maintaining a

convincing facade seems to be difficult to sustain. Note

especially Clinton whose levels of persona deception drop

sharply. This can be mapped quite directly to changes in

0 50 100 150 200 250 300 350 400 450−0.2

−0.15

−0.1

−0.05

0

0.05

0.1

0.15Fig. 29 Trend in negative

words with time for all

candidates


123


strategy: in the early primary, she tried to be the most

knowledgeable candidate (and so high exclusive word use);

later she reached out directly to her supporter base with

highly personal speeches (and so high incidence of first-

person singular pronouns) (Fig. 32).

4.8 Integrative complexity

Integrative complexity and its component constructs show

the structural complexity of discussion that each candidate

is using. This is presumably a blend of their own personal

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i−PPSS

i’ve−PPSS

my−PP$

i’m−PPSS

but−CC

although−CS unless−CS

nor−CC

me−PPO

rather−QL however−RB

without−IN

i’d−PPSS rather−RB except−IN jerk−VB follow−VB

me−VBD lies−VBZ mine−NN me−VB or−NIL however−WRB move−NN inadequate−JJ go−UH hate−NN lies−NNS but−IN rather−IN run−VBN sorry−JJ me−NN go−NN worthless−JJ go−RB lie−NN whereas−CS hate−JJ besides−RB my−NN dumb−JJ mine−NP followed−VBN me−VBN stressed−VBN hates−VBZ me−NPS wicked−JJ greed−VBN me−NIL despise−VB taking−NIL lead−VBN hated−VBN or−VB inferior−JJ dislike−VB my−JJ my−NIL lie−NP i−NP hated−VBD lied−VBN disappointing−JJ go−NP fled−VBN my−NP followed−VBD i−NIL except−RB however−WQL walk−NN mine−VB vain−JJ ignorant−JJ go−NP$ carrying−VBG arrived−VBN arrives−VBZ anger−NN but−NIL moved−VBN greed−VBD arrive−VB lonely−JJ

lead−NN besides−IN go−NIL enemy−NN look−NN arrived−VBD lie−VB mine−PP$$

i’ll−PPSS

flew−VBD hate−VB drive−NN crazy−JJ greed−NN afraid−JJ run−NN weak−JJ goes−VBZ fear−VB

myself−PPL

walk−VB moved−VBD driven−VBN drive−VB terrible−JJ

go−VB

carry−VB abandon−VB tragedy−NN fear−NN disappointed−VBN loss−NN action−NN

run−VB

bringing−VBG move−VB

look−VB

lead−VB

going−VBG

taking−VBG take−VB

or−CC

v1

v2


deceptive words

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Fig. 32 Persona deception

variation by time


123


level of sophistication about issues, and their judgements

about the level of sophistication available to or desired by

their audiences.

Figure 34 shows the integrative complexity values for

each of the speeches arranged by candidate. Note that there

is considerable variation from speech to speech, which is

often, particularly in the late stages of a campaign, from

day to day or even from hour to hour. This suggests that

there is considerable low-level alteration in speeches at or

close to the moment of delivery.

0 50 100 150 200 250 300 350 400 450−0.25

−0.2

−0.15

−0.1

−0.05

0

0.05

0.1

0.15

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deception over time for all

candidates

0 50 100 150 200 250 300 350 400 450

1.4

1.6

1.8

2

2.2

2.4

2.6

2.8Fig. 34 Integrative complexity

by candidate and time


123


As expected, integrative complexities tend to drop in the

later stages of a campaign, but with a slight tendency to

increase in the very last part.

Figures 35 and 36 show how the overall integrative

complexity depends on elaboration and dialectical com-

plexity. Generally speaking, the decrease in integrative

0 50 100 150 200 250 300 350 400 4501.1

1.2

1.3

1.4

1.5

1.6

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1.9

2

2.1Fig. 35 Elaboration by

candidate and time

0 50 100 150 200 250 300 350 400 4501

1.2

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1.6

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2

2.2

2.4Fig. 36 Dialectical complexity

by candidate and time


123


complexity in the late stages comes from both reduced

elaboration and reduced dialectical complexity, rather than

from one or the other. It is clear, however, that much of

Obama’s greater integrative complexity in the 2012 cam-

paign comes from greater elaboration.

5 Discussion and conclusions

We now return to consider our hypotheses in the light of

these empirical results.

Our first hypothesis was that influencers would exhibit

consistency across time. There is some evidence to support

this over medium time scales—the temporal sequences for

most candidates and most channels remained in the same

region of the semantic space created from the global use of

each channel. However, it is clear that there is high vari-

ation over short time scales, up to a few days. Either the

process by which speechwriters create speeches is inher-

ently variable over short time scales; or candidates are

unable to sustain ‘the same’ word patterns from day to day.

This latter could be simply boredom, but it could also be a

function of campaign speeches that are inherently artificial,

so candidates have difficulty maintaining consistency.

Persona deception is one area where this is more likely—

there is some evidence that people have difficulty main-

taining facades over time. The most striking aspect of this

lack of consistency is that the speeches used from day to

day seem, to a human reader, to be essentially the same—

that is, they are based on the same template. The apparent

variation must, therefore, be the accumulation of many

small changes rather than a few large ones.

Our second hypothesis was that influencers would

attempt to differentiate themselves from their competitors

to the greatest extent possible. This is not well supported

by the data: there are differences between the two parties,

and some small differences among candidates but the

greatest difference, across almost all channels, is between

Obama in 2008 and Obama in 2012.

For differentiation based on usage of nouns, there are

differences by party, and also differences based on the

broader environment in which each election took place—

for example, the use of words such as ‘‘crisis’’ in 2008 but

not in 2012, and the overall emphasis on financial and

economic topics in 2008 but not in 2012. For adjective and

verb use, there are also visible differences among candi-

dates and across time; this is much weaker for adverbs.

For both positive and negative words, there is little

evidence to suggest differentiation among candidates, and

very little sign of consistency in areas where it might have

been expected. It is not only difficult for campaigns to

maintain positive language, which is perhaps not altogether

surprising, but also difficult for them to maintain negative

language, which is perhaps more surprising. There is little

support for the conventional wisdom that challengers tend

to be more negative than incumbents but, of course, only

one candidate in this set is an incumbent.

Persona deception is one area where there are clear

differences among candidates, as expected. Maintaining a

persona better than one’s real personality is plausibly dif-

ficult, so it is not surprising that there is considerable short-

term variation in this area. There are also noticeable dif-

ferences in ‘baseline’ ability in this area too. Once again,

we see that Obama maintains similar (although slightly

reduced) levels of persona deception between 2008 and

2012, but uses a different pattern of the underlying words

of the model.

For integrative complexity, we see, as expected, reduc-

tions in the later stages of campaigns, although with a

consistent slight rise in the very late stages which begs an

explanation. It is somewhat surprising that, in a close and

hard-fought election, increases in dialectic differentiation

do not come into play as the result of attempts to draw

distinctions between candidates’ positions.

Overall the greatest difference between any two cam-

paigns from the perspective of language use is that between

the 2008 Obama campaign and the 2012 Obama campaign.

These differences were not in substantive directions—

rather they seemed to be orthogonal to dimensions in which

variation related to substantive ideas appeared. This

remains puzzling, given that his speechwriting teams had

substantial overlap, including especially the pervasive

presence of Jon Favreau as lead speechwriter; and that a

study comparing his language patterns as 2008 candidate

and then sitting president showed little difference (Olson

et al. 2012).

Finally, since Obama was the successful candidate in

both of these election cycles, it may be instructive to

consider his language patterns overall. These are shown in

Table 4.

Table 4 Obama’s usage of the eight channels—the recipe for

success?

Channel Obama’s usage

Nouns Process nouns

Adjectives Category adjectives

Verbs ‘‘Go’’, ‘‘get’’, ‘‘want’’

Adverbs ‘‘Back’’, ‘‘now’’

Positive Midrange

Negative Midrange, highly variable

Persona deception High levels, few first-person

singular pronouns

Integrative complexity Decreasing


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Politicians are good surrogates for more general influ-

encers because they are highly motivated and well funded,

because they must attempt to influence many people in

varied settings, and because they cannot appeal only to

those who are already willing to be influenced. The

approach, and perhaps many of the results, presented here

can be applied to other influence settings such as adver-

tising and terrorism. Recall that our goal is not so much to

understand the process, although we do gain some insight,

but to extract information about the influencers from their

use of the process.

6 Related work

There is a large literature on sentiment analysis (e.g.,

Tetlock 2007; Whitelaw et al. 2005; Kanayama et al. 2004;

Nasukawa and Yi 2003; Godbole et al. 2007) including

attempts to predict election outcomes (Tumasjan et al.

2010). That work addresses the converse of the problem we

address here: how to understand the reaction of an audi-

ence to the effects of an influencer.

There is also a voluminous literature on the interaction

between politics and language, addressing issues such as

how the choice of particular words frames a political dis-

course, how words change with political changes, and how

politicians can be better salespeople. This work is orthog-

onal to the problem we address here, since it is primarily

concerned with improving the process of influencing.

The work closest to ours is work by psychologists who

have investigated the relationship between language use

and mental state, e.g., Chung and Pennebaker’s work

(Chung and Pennebaker 2008; Chung and Pennebaker

2007) on how words reveal psychological profiles and

health; Newman and Pennebaker’s work on deception

(Newman et al. 2003), and Tausczik and Pennebaker’s

recent survey (Tausczik and Pennebaker 2010). Attempts

to identify ideology from language usage, e.g., Koppel

et al. (2009), are also relevant.

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