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Social Media Analytics: Concepts, Models, Methods , & Tools

Social Media Week: Copenhagen

Social Media Analytics: Concepts, Models, Methods, Tools

Solbjerg Plads 3, 2.01; Frederiksberg

21-Feb-2014

Ravi Vatrapu

Professor mso, Department of IT Management, Copenhagen Business School

Director, Computational Social Science Laboratory (CSSL),

Professor of Applied Computing, Norwegian School of Information Technology (NITH)

Email: vatrapu@cbs.dk

with

Daniel Hardt

Raghava Rao Mukkamala

Abid Hussain

Chris Zimmerman

Niels Buus Lassen

René Madsen

Kjeld Hansen

Kiran Kumar Kocherla

WORKSHOP PROGRAM

13:00-13:30: Social Data Analytics

Concepts

Models

13:30-14:15: Empirical Studies: Methods

Social Data Analytics: US elections 2008 & Danish elections 2011

Exploratory Analysis: e-shop visits, e-shop sales, & social media actions

Correlational Analysis: revenues, social graph, & social text

Fuzzy Set Sentiment Analysis: real-world events and social media sentiments

Predictive Analytics: iPhone sales and tweets (René Madsen & Niels Buus Lassen)

14:15-14:30: BREAK

14:30-15:45: Interactive Demos: Tools

Social Data Analytics Tool (SODATO) (Abid Hussain)

Danish Sentiment Analysis Tool (Daniel Hardt)

Visual Analytics: Tableau: #Marius (Chris Zimmerman)

15:45-16:00: Plenary Discussion

Workshop Conclusion

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SOCIAL MEDIA ANALYTICS: METHODOLOGICAL FRAMEWORK

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TECHNOLOGIES OF PRACTICAL REASON (FOUCAULT, M., MARTIN, L. H., GUTMAN, H., & HUTTON, P. H. (1988). TECHNOLOGIES OF THE SELF: A SEMINAR WITH MICHEL FOUCAULT: UNIV OF MASSACHUSETTS PRESS.)

Four Matrices of Practical Reason

Technologies of Production

Technologies of Sign Systems

Technologies of Power

Technologies of the Self

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Social Computing (Wang et al., 2007)

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SOCIAL BUSINESS

”A Social Business is an organization that strategically engages, analyses and manages social media to structure organizational processes and support organizational functions in order to realize operational efficiencies, generate competitive advantages and create value for customers, share holders and other societal stakeholders.

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SOCIAL BUSINESS

Three critical aspects of Social Business – Social Media Engagement (SmE):

Organization's strategic use of social media channels to interact with its internal and external stakeholders for the purposes ranging from marketing, customer support, product development and knowledge management.

– Social Media Analytics (SmA)

Collection, storage, analysis and reporting of social data emanating from the social media engagement of and social media conversations about the organization.

– Social Media Management (smM)

SMM focuses on the operational issues, managerial challenges and comparative advantages with respect to the emerging paradigm of Social Business

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Part I: Social Data Theory

Outline of a Theory of Socio-Technical Interactions (Vatrapu, R. (2010). Explaining culture: an outline of a theory of socio-technical interactions. Proceedings of the 3rd ACM International Conference on Intercultural Collaboration (ICIC 2010), 111-120)

Social: other-orientation & other-involvement

Technology: place-shifting & time-shifting

Socio-Technical Systems involve:

Interacting with Technologies

Interacting with Others via Technologies

Interacting with Technologies

Perception of Affordances

Appropriation of Affordances

Interacting with Others via Technologies

Structures of Technological Intersubjectivity

Functions of Technological Intersubjectivity

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Perception of Affordances

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Appropriation of Affordances Youtube: “Gods Must Be Crazy” + “Coke Bottle”

http://www.youtube.com/watch?v=17HGR7FBwu0

TECHNOLOGICAL INTERSUBJECTIVITY

• Production, Projection, and Performance of Intersubjectivity

• How actors interact with, relate to, and form impressions of each other

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"Piled Higher and Deeper" by Jorge; www.phdcomics.com. Image used with permission.

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Part II: Social Data Models

CONCEPTUAL MODEL: SOCIAL GRAPH + SOCIAL TEXT

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Appropriation of Affordances Technological Intersubjectivity

FORMAL MODEL: SET THEORY

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• Mathematics: Fuzzy Set Logic instead of Graph Theory

• Social Attribute: Associations instead of Relations

• Social Grouping: Sets instead of Social Networks

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Part III: Methods

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Study #1 Social Data Analytics: Political Science

Hussain, A., Vatrapu, R., Hardt, D., & Jaffari, Z. (in press/2014). Social Data Analytics Tool: A

Demonstrative Case Study of Methodology and Software. In Gibson, R. (ed). Analysing Social Media

Data and Web Networks. Palgrave Macmillan.

Robertson, S., Vatrapu, R., & Medina, R. (2010). Off the wall political discourse: Facebook use in the

2008 U.S. presidential election. Information Polity, 15(1,2), 11-31.

Robertson, S., Vatrapu, R., & Medina, R. (2010). Online Video “Friends” Social Networking:

Overlapping Online Public Spheres in the 2008 U.S. Presidential Election. Journal of Information

Technology & Politics, 7(2-3), 182-201. doi: 10.1080/19331681003753420

Robertson, S. P. (2011). Changes in referents and emotions over time in election-related social

networking dialog. In System Sciences (HICSS), 2011 44th Hawaii International Conference on (pp.

1-9). IEEE.

FRAMEWORK: ENGAGEMENT DIMENSIONS

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SOCIAL NETWORK DIALOG SPACE

Robertson, S., Vatrapu, R., & Medina, R. (2010). Off the Wall Political Discourse: Facebook Use in the 2008 U.S.

Presidential Election. Information Polity, 15(1-2), 11-31.

RESULTS: SOCIAL GRAPH: DK 2011: WALL CROSSING

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SOCIAL TEXT ANALYSIS

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Robertson, S. (2010). Changes in Referents and Emotions Over Time in Election-Related Social Networking Dialog. Proceedings of

HICSS 2010

Reflection-to-Selection Hypothesis

change from first-person and second-person pronoun usage to third-person pronoun usage as an election approaches

Converging Sentiment Hypothesis

the amount of positive and negative discourse begins to equalize as participants in political discourse begin to divide their time, and their comments, between their own candidate and group and their competitors’ candidates and groups.

RESULTS: SOCIAL TEXT: US 2008: PRONOUN USAGE: OBAMA

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Robertson, S. (2010). Changes in Referents and Emotions Over Time in Election-Related Social Networking Dialog.

Proceedings of the 44th Annual Meeting of the Hawaii International Conference on Systems Sciences (HICSS44), IEEE, .

Percentage of words in the first-person, second-person, and third-person categories for Barack Obama

RESULTS: SOCIAL TEXT: DK 2011: PRONOUN USAGE: HELLE

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Percentage of words in the first-person, second-person, and third-person categories for Helle Thorning-Schmidt

0

0,005

0,01

0,015

0,02

0,025

0,03

1 2 3 4 5 6 7 8 9 10 11 12 13

Helle Pronouns

first person

second person

third person

RESULTS: SOCIAL TEXT: US 2008: SENTIMENT: OBAMA

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Robertson, S. (2010). Changes in Referents and Emotions Over Time in Election-Related Social Networking Dialog.

Proceedings of the 44th Annual Meeting of the Hawaii International Conference on Systems Sciences (HICSS44), IEEE, .

Percentage of Sentiment Words for Barack Obama

RESULTS: SOCIAL TEXT: DK 2011: SENTIMENT: HELLE

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Percentage of words in the first-person, second-person, and third-person categories for Helle Thorning-Schmidt

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1 2 3 4 5 6 7 8 9 10 11 12 13

Helle Sentiment

Positive

Negative

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Study #2 Exploratory Analysis: e-Commerce

E-Shop Sales, Website Visits, Social Media Engagement

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Master Thesis of Julie Redlef Kristiansen, ITU

2013-01 2013-02 2013-03 2013-04 2013-05 2013-06 2013-07 2013-08 2013-09 2013-10 2013-11 2013-12

FBPosts 8 17 11 7 10 11 3 14 18 19 10 33

FBLike 126 199 133 68 133 170 57 291 237 188 162 280

FBComments 6 14 2 0 8 7 0 1 2 2 0 16

instagramposts 2 10 9 7 13 9 14 17 13 14 14 10

InstagramLikeCount 56 576 394 247 928 352 729 1381 839 1714 909 840

instagramCommentCount 3 34 18 6 44 12 40 64 34 124 46 26

eShop 1460,1 1269 1313,4 1370,9 1602,2 1450,8 1040,5 1528 1192,1 1057 1499,5 87,5

Sales 3809,5 4433,1 2414 4675 4375 6241,6 2742,8 5504 4213 3081 5915 399,1

0

1000

2000

3000

4000

5000

6000

7000

Monthly

E-Shop Sales, Website Visits, Social Media Engagement

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Master Thesis of Julie Redlef Kristiansen, ITU

Sunday Monday Tuesday Wednesday Thursday Friday Saturday

FBPosts 9 72 66 58 43 72 7

FBLike 130 554 650 537 380 686 52

FBComments 14 29 107 21 12 37 4

instagramposts 1 21 24 28 28 31 5

InstagramLikeCount 102 1009 1347 1505 2192 2588 279

instagramCommentCount 0 40 98 53 118 122 20

ShopVisit 500,13 599,51 596,1 563,19 547,81 512,3 444,28

Revenue 1431,89 2065,39 2106,96 1863,62 1655,31 1517,18 1008,51

0

500

1000

1500

2000

2500

3000

Day of the week

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Study #3 Correlational Analysis: revenues & facebook activity

Sales & Social: Quarterly

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• Social Data Analytics Tool (SODATO) used to collect facebook data of H&M

• Time Period: 01-Jan-2009 to 31-July-2013

• Corpus:

• 100,465 posts

• 262,588 comments on posts

• 7, 779,411 likes on posts and comments

• 3,134,249 unique facebook ids/users

• 18 quarterly sales numbers

• Investigated statistical correlation between social data measures and revenues

• We found statistically significant correlations for quarterly sales with

• Measures of social graph (posts, likes, comments)

• Measures of social text (positive, negative or neutral sentiment expressions

in posts and comments).

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Study #4 Exploratory Analysis: Fuzzy Sentiment Analysis

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Study #5 Predictive Analytics: iPhone: sales and tweets

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BREAK

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Part IV: Tools

“Show me the demos”

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Tool #1 Social Data Analytics Tool (SODATO)

SODATO: Introduction

Purpose is to analyse social data systematically

Designed for research projects

Technical architecture and technological infrastructure Multiple simultaneous data fetch requests (multi threading)

Self-aware of the status of fetch requests and will trigger data aggregation and the metric engine accordingly

Console based Fetch

Aggregation and Data Export to handle large amounts of data

Email notifications

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SODATO: History

From SOGATO, 2011 Hussain, A., & Vatrapu, R. SOGATO: A Social Graph Analytics Tool . Demo at the 12th European

Conference on Computer Supported Cooperative Work (ECSCW), 2011.

To SODATO, 2013 Hussain, A., Vatrapu, R., Hardt, D., & Jaffari, Z. (in press/2014). Social Data Analytics Tool (SODATO):

Description and Application to Danish Elections 2011. in Gibson, R et al. (eds). Digital Methods for Politics.

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SOGATO: Old Architecture

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SODATO: Current Architecture

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”Show me the demo!”

http://tinyurl.com/sodato

Username: SMWeek

Password: SMWeek

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Tool #2 Danish Sentiment Analysis

http://tinyurl.com/danishsentiment

In your opinion, this text is: Hvor er retfærdigheden for dette smukke dyr? Disse syge mennesker skulle

myrdes på samme måde, som Marius blev

A. Positive

B. Negative

C. Neutral

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Positiv

e

Negat

ive

Neutra

l

33%33%33%

In your opinion, this text is: Okay det er i orden at gå ovenpå en død hval, men så snart en zoo skærer en giraf op

og giver til havens dyr, så flipper dk ud

A. Positive

B. Negative

C. Neutral

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Positiv

e

Negat

ive

Neutra

l

33%33%33%

In your opinion, this text is: Giraf skal aflives Her er Marius, der til daglig bor i Zoologisk Have. Han fejler ikke

noget. Men han skal alligevel aflives på søndag.

A. Positive

B. Negative

C. Neutral

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Positiv

e

Negat

ive

Neutra

l

33%33%33%

In your opinion, this text is: Torsdagens russiske aviser revser deres egne ishockeymænd, efter at de led et smerteligt nederlag på 1-3 til deres finske naboer I kvartfinalen ved OL-turneringen. 'Skamfuldt for en verdensmagt',mente Sovietsky Sport, 'Brændt i finsk sauna', skrev Kommersant, mens avisen Izvestia bedyrede, at 'Rusland ikke viste sit fulde potentiale'.

A. Positive

B. Negative

C. Neutral

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Positiv

e

Negat

ive

Neutra

l

0%0%0%

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Tool #3 Visual Analytics: #Marius

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#Marius: Timeline

http://tinyurl.com/mariustimeline

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#Marius: Tableau Visualizations

http://tinyurl.com/mariusvisual

Part V: CBS & You “freemium” Engaged Scholarship Model

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NETWORKED BUSINESS PROJECT 2014-1017

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Survey of Perceptions, Practices, and

Value Generation with Social Media,

Mobile, and Cloud Computing

2729 Respondents/Orgnaizations

Private: 2432

Public: 297

Software: Social Data Analytics Tool

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Workshop: Danish Sentiment Analysis

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ABID HUSSAIN: PHD PROJECT: SOCIAL DATA ANALYTICS

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CHRIS ZIMMERMAN: INDUSTRIAL PHD PROJECT: SOCIAL BUSINESS INTELLIGENCE

KATRINE KUNST: TDC PHD PROJECT: SOCIAL CONSUMPTION

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SOLEY RASMUSSEN: INDUSTRIAL PHD PROJECT: NEWS-AS-A-SERVICE

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ZESHAN JAFFARI: PHD PROJECT: SOCIAL BUSINESS MANAGEMENT

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KOSTAS PANTAZOS: POST DOC PROJECT : INTERACTIVE DASHBOARDS

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Discussion

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vatrapu@cbs.dk