20111123 mwa2011-marc smith

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Presentation to Mobile Web Africa 2011 in Johannesburg, South Africa.

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Marc A. SmithChief Social ScientistConnected Action Consulting Groupmarc@connectedaction.nethttp://www.connectedaction.nethttp://www.codeplex.com/nodexl

A project from the Social Media Research Foundation: http://www.smrfoundation.org

Charting Collections of Connections in Social

Media: Creating Maps and

Measures with NodeXL

About Me

Introductions

Marc A. SmithChief Social ScientistConnected Action Consulting Group

Marc@connectedaction.nethttp://www.connectedaction.nethttp://www.codeplex.com/nodexlhttp://www.twitter.com/marc_smithhttp://delicious.com/marc_smith/Paper http://www.flickr.com/photos/marc_smithhttp://www.facebook.com/marc.smith.sociologisthttp://www.linkedin.com/in/marcasmithhttp://www.slideshare.net/Marc_A_Smithhttp://www.smrfoundation.org

Location, Location, Location

Network of connections among “SharePoint” mentioning Twitter users

Position, Position, Position

Hardin, Garrett. 1968/1977. “The tragedy of the commons.” Science 162: 1243-48. Pp. 16-30 in Managing the Commons, edited by G. Hardin and J. Baden. San Francisco: Freeman.

Wellman, Barry. 1997. “An electronic group is virtually a social network.” In S. Kiesler (Ed.), The Culture of the Internet. Hillsdale, NJ: Lawrence Erlbaum.

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Collective Action Dilemma Theory

• Central tenet– Individual rationality leads to collective disaster

• Phenomena of interest– Provision and/or sustainable consumption of collective

resources– Public Goods, Common Property, "Free Rider” Problems,

Tragedies– Signaling intent

• Methods– Surveys, interviews, participant observation, log file analysis,

computer modeling

(Axelrod, 1984; Hess, 1995; Kollock & Smith, 1996)

Community Computer Mediated Collective Action

Common goods that require controlled consumption

http://flickr.com/photos/himalayan-trails/275941886/

Common goods that require collective contribution

http://flickr.com/photos/jose1jose2jose3/241450368/

Interactionist Sociology

• Central tenet– Focus on the active effort of

accomplishing interaction• Phenomena of interest

– Presentation of self – Claims to membership– Juggling multiple (conflicting) roles– Frontstage/Backstage – Strategic interaction– Managing one’s own and others’ “face”

• Methods– Ethnography and participant observation

(Goffman, 1959; Hall, 1990)

Whyte, William H. 1971. City: Rediscovering the Center. New York: Anchor Books.

Youse.Y’all.

Yes, youse.

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Are you my friend?

yes no

I like you I really like youI kind of like you

I feel socially obligated to link to youI know you

I wish I knew you I like your picture You are cool

I was paid to link to you I want your reflected glory

Everybody else links to you I’d vote for you

We met at a conference and it seemed like the thing to do.

Can I date you?

I beat you on Xbox Live Hi, Mom I have fake alter egos

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Tag Ecologies I

Adamic et al. WWW 2008

HUB-AND-SPOKE OF DECEIT: When Enron employees communicated about legitimate projects, e-mails were reciprocal and information was shared widely (right), but communications about an illicit project (left) reveal a sparse network with a central, informed clique and isolated external players.Brandy Aven, CMUhttp://www.sciencenews.org/view/generic/id/330731/title/Information_flow_can_reveal_dirty_deeds

Networks reveal patterns

Social Media (email, Facebook, Twitter, YouTube, and more) is all about connections

from people to people.

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Patterns are

left behind

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There are many kinds of ties….

http://www.flickr.com/photos/stevendepolo/3254238329

Like, Link, Reply, Rate, Review, Favorite, Friend, Follow, Forward, Edit, Tag, Comment, Check-in…

World Wide Web

Each contains one or more social networks

Hubs

Bridges

http://www.flickr.com/photos/library_of_congress/3295494976/sizes/o/in/photostream/

Clusters

http://www.flickr.com/photos/amycgx/3119640267/

Crowds

20111122-NodeXL-Twitter-mwa11 OR mwa2011 OR mwebafrica OR mobilewebafrica

20111121-NodeXL-Twitter-#occupywallstreet

20111122-NodeXL-Twitter-malema

Won Soon Park, New Mayor of Seoul Korea

• Central tenet – Social structure emerges from – the aggregate of relationships (ties) – among members of a population

• Phenomena of interest– Emergence of cliques and clusters – from patterns of relationships– Centrality (core), periphery (isolates), – betweenness

• Methods– Surveys, interviews, observations,

log file analysis, computational analysis of matrices

(Hampton &Wellman, 1999; Paolillo, 2001; Wellman, 2001)

Source: Richards, W. (1986). The NEGOPY network analysis program. Burnaby, BC: Department of Communication, Simon Fraser University. pp.7-16

Social Network Theoryhttp://en.wikipedia.org/wiki/Social_network

SNA 101• Node

– “actor” on which relationships act; 1-mode versus 2-mode networks• Edge

– Relationship connecting nodes; can be directional• Cohesive Sub-Group

– Well-connected group; clique; cluster• Key Metrics

– Centrality (group or individual measure)• Number of direct connections that individuals have with others in the group (usually look at

incoming connections only)• Measure at the individual node or group level

– Cohesion (group measure)• Ease with which a network can connect• Aggregate measure of shortest path between each node pair at network level reflects

average distance– Density (group measure)

• Robustness of the network• Number of connections that exist in the group out of 100% possible

– Betweenness (individual measure)• # shortest paths between each node pair that a node is on• Measure at the individual node level

• Node roles– Peripheral – below average centrality– Central connector – above average centrality– Broker – above average betweenness

E

D

F

A

CB

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CD

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A B D E

http://www.flickr.com/photos/marc_smith/sets/72157622437066929/

20110315-NodeXL-Twitter-sxsw graph

Welser, Howard T., Eric Gleave, Danyel Fisher, and Marc Smith. 2007. Visualizing the Signatures of Social Roles in Online Discussion Groups. The Journal of Social Structure. 8(2).

Experts and “Answer People”

Discussion starters, Topic setters

Discussion people, Topic setters

AnswerPerson

Signatures

DiscussionPeople

Now Available

Analogy: Clusters Are OccludedHard to count nodes, clusters

Separate Clusters Are More Comprehensible

Twitter Network for “Microsoft Research”*BEFORE*

Twitter Network for “Microsoft Research”*AFTER*

Goal: Make SNA easier

• Existing Social Network Tools are challenging for many novice users

• Tools like Excel are widely used• Leveraging a spreadsheet as a host for SNA

lowers barriers to network data analysis and display

Social Media Research Foundationhttp://smrfoundation.org

What we are trying to do:Open Tools, Open Data, Open Scholarship

• Build the “Firefox of GraphML” – open tools for collecting and visualizing social media data

• Connect users to network analysis – make network charts as easy as making a pie chart

• Connect researchers to social media data sources• Archive: Be the “Allen Very Large Telescope Array”

for Social Media data – coordinate and aggregate the results of many user’s data collection and analysis

• Create open access research papers & findings• Make “collections of connections” easy for users to

manage

What we have done: Open Tools

• NodeXL• Data providers (“spigots”)

– ThreadMill Message Board– Exchange Enterprise Email– Voson Hyperlink– SharePoint– Facebook– Twitter– YouTube– Flickr

What we have done: Open Data

• NodeXLGraphGallery.org– User generated collection of

network graphs, datasets and annotations

– Collective repository for the research community

– Published collections of data from a range of social media data sources to help students and researchers connect with data of interest and relevance

What we have done: Open Scholarship• Webshop 2011: NSF, Google, Intel

– 4 Days, 45 Students, 20 Speakers– Great tweets!

• Webshop 2012!– Expand numbers of students and add a day– Support speakers and student workers

• Workshops: Purdue, Maryland, Cape Town, Yeungnam

What we have done: Open Scholarship

Facebook networkshttp://www.connectedaction.net/2010/04/25/bernie-hogans-facebook-social-network-data-provider-and-visualization-toolkit/

NodeXL data import sources

Example NodeXL data importer for Twitter

NodeXL imports “edges” from social media data sources

NodeXL Automation makes analysis simple and fast

NodeXL Network Metrics

NodeXL simplifies mapping data attributes to display attributes

NodeXL displays subgraph images along with network metadata

NodeXL enables filtering of networks

NodeXL Generates Overall Network Metrics

What we want to do: (Build the tools to) map the social web• Move NodeXL to the web:

– Node for Google Doc Spreadsheets!– WebGL Canvas

• Connect to more data sources of interest:– RDF, MediaWikis, Gmail, NYT, Citation Networks

• Solve hard network manipulation UI problems:– Modal transform, Time series, Automated layouts

• Grow and maintain archives of social media network data sets for research use.

• Improve network science education:– Workshops on social media network analysis– Live lectures and presentations– Videos and training materials

Work ItemsAutofill Group AttributeMerge Edges by AttributeModal TransformMerge WorkbooksAutomated Dynamic Filters: Time Series Analysis, contrastCaptions and LegendsUpload to Graph Gallery++: captions, workbookGraph Gallery++

User Accounts, Reporting, RSS Feeds, Network Visualization Web Canvas

Import: RDF, Wiki, SharePoint, Keyword networks from textMetrics: Triad CensusLayouts:

Force Atlas 2, Lin Log, “Bakshy Plots”, Quality MeasuresQuery-by-example search for network structures

How you can help

• Sponsor a feature• Sponsor Webshop 2012• Sponsor a student• Schedule training• Sponsor the foundation• Donate your money, code, computation, storage,

bandwidth, data or employee’s time• Help promote the work of the Social Media

Research Foundation

20111122-NodeXL-Twitter-poib

20111122-NodeXL-Twitter-zuma

Social Network Maps Reveal

Key influencers in any topic.

Sub-groups.

Bridges.

Why didn’t you just say so?

Identify the key influencers in any topic.Netbadges awards badges to influential people and web sites on the Internet. We analyze the social network of connections among all the

people or web sites that gather around a topic, issue, or interest and award badges to key people and sites, highlighting their recent

content.

Contact:

Marc A. SmithChief Social ScientistConnected Action Consulting Group

Marc@connectedaction.nethttp://www.connectedaction.nethttp://www.codeplex.com/nodexlhttp://www.twitter.com/marc_smithhttp://delicious.com/marc_smith/Paper http://www.flickr.com/photos/marc_smithhttp://www.facebook.com/marc.smith.sociologisthttp://www.linkedin.com/in/marcasmithhttp://www.slideshare.net/Marc_A_Smithhttp://www.smrfoundation.org

Cape Town28 November 2011

Protea HotelBreakwater Lodge,

Waterfront

Johannesburg30 November 2011

Gordon Instituteof Business Science,

Illovo

UpcomingFull-day social media network analysis workshops

This Friday – Hands on with NodeXL

Next week

Marc Smith Walter Pike

Marc A. SmithChief Social ScientistConnected Action Consulting Groupmarc@connectedaction.nethttp://www.connectedaction.nethttp://www.codeplex.com/nodexl

A project from the Social Media Research Foundation: http://www.smrfoundation.org

Charting Collections of Connections in Social

Media: Creating Maps and

Measures with NodeXL

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