All Contents © 2010 Burton Group. All rights reserved.

Trends In Social Networking

Thursday – 29 July, 2010Mike Gotta

Research VP

Collaboration & Content

mike.gotta@gartner.com

Trends In Social Networking

Dr. Marc A. SmithChief Social Scientist, Connected Action Consulting Group• Marc Smith is a sociologist specializing in the social organization of online

communities and computer mediated interaction. He founded and managed the Community Technologies Group at Microsoft and led the development of social media reporting and analysis tools for Telligent Systems.

• Smith now leads the Connected Action consulting group. The Connected Action consulting group applies social science methods in general and social network analysis techniques in particular to enterprise and internet social media usage.

• Smith also co-founded the Social Media Research Foundation, a non-profit devoted to open tools, data, and scholarship related to social media research.

• Smith received a B.S. in International Area Studies from Drexel University in Philadelphia in 1988, an M.Phil. in social theory from Cambridge University in 1990, and a Ph.D. in Sociology from UCLA in 2001. He is an affiliate faculty at the Department of Sociology at the University of Washington and the College of Information Studies at the University of Maryland. Smith is also a Distinguished Visiting Scholar at the Media-X Program at Stanford University.

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Trends In Social Networking

Dr. Marc A. SmithChief Social Scientist, Connected Action Consulting Group• marc@connectedaction.net• http://www.connectedaction.net• http://nodexl.codeplex.com• http://twitter.com/marc_smith• http://www.smrfoundation.org/

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Trends In Social Networking

Agenda

• The state of social network analysis (SNA)• Graph engines, API’s, and standards• How-to guide to analyzing networks

• Risks – the dark side of SNA• Risks to privacy, confidentiality…

• Implications to the IT organization• Skill sets, data management strategies

• Social Media & SNA• Impact of social media on SNA• Visualization of Twitter posts referencing #CAT10

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S o c i a l M e d I a R e s e a r c hF o u n d a t i o n

Open ToolsOpen DataOpen Scholarship

http://smrfoundation.org

http://connectedaction.net

Enterprise Internet

Social media network analysis

World Wide Web

Each contains one or more social networks

Location, Location, Location

ecommNetwork of connections among “ecomm” mentioning Twitter users

Position, Position, Position

Network Overview, Discovery, and Exploration for Excel 2007 and 2010

Free and open codehttp://nodexl.codeplex.com

All Contents © 2010 Burton Group. All rights reserved.

The NodeXL Project Team

A minimal network can illustrate the ways different

locations have different values for centrality and

degree

Diane h

as hi

gh

degre

e

Heather has high

betweeness

NodeXLNetwork Overview Discovery and Exploration add-in for Excel 2007

Import from multiple social media network

sources

Import from multiple social media network

sources

NodeXL: data providers for social media networks

NodeXL: Mapping connections among people who tweet “#CAT10” – July 27, 2010

NodeXL: Lists of most “between” users in “#CAT10” twitter population on July 26, 2010

18NodeXL: Mapping connections among people who tweet “#CAT10” – July 29, 2010

19NodeXL: Mapping connections among highly between people who tweet “#CAT10” – July 29, 2010

20NodeXL: Mapping connections among most highly between people who tweet “#CAT10” – July 29, 2010

21NodeXL: Lists of most “between” users in “#CAT10” twitter population on July 29, 2010

NodeXL: Mapping connections among highly between people who tweet “SCRM” – July 29, 2010

Social network analysis of email lists: highlight key roles

Social network analysis of 2007 US Senate voting network

Communities in Cyberspace

Forthcoming, Summer 2010

I. Getting Started with Analyzing Social Media Networks 1. Introduction to Social Media and Social Networks 2. Social media: New Technologies of Collaboration 3. Social Network Analysis

II. NodeXL Tutorial: Learning by Doing 4. Layout, Visual Design & Labeling 5. Calculating & Visualizing Network Metrics 6. Preparing Data & Filtering 7. Clustering &Grouping

III Social Media Network Analysis Case Studies 8. Email 9. Threaded Networks 10. Twitter 11. Facebook 12. WWW 13. Flickr 14. YouTube 15. Wiki Networks

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

H

G

I

CD

E

A B D E

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

Distinguishing attributes of online social roles

Answer person• Outward ties to local isolates• Relative absence of

triangles• Few intense ties

Reply Magnet• Ties from local isolates often

inward only• Sparse, few triangles• Few intense ties

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The State Of Social Network Analysis

Topic: State Of The Market & Profession

• What’s our current understanding of social networks and SNA?• What’s emerging in terms of graph engines and standards

that we should know and care about?• Sunbelt 2010 conference just concluded – findings?

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The State Of Social Network Analysis

Topic: Risks – The Dark Side of Social Networks & SNA

• With all this social data out in the public – what are the risk aspects we need to be concerned about?

• Social network sites like Facebook and LinkedIn• Social media and the impact of Twitter• Social feedback (ratings, “like”, “favorite”, ranking, tags…)• Mobility and use of location data• Connecting identity facets and correlating the results (e.g., social roles)

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The State Of Social Network Analysis

Topic: Implications of SNA to the IT organization

• How do social networks, SNA, and the collection of massive amounts of social data mean to data management strategies (e.g., business intelligence, “data clouds”)?

• Related enterprise concerns:• Intellectual property• Confidentiality• Privacy• Compliance

• What skills are now needed for IT organizations to play a role in SNA?

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The State Of Social Network Analysis

Topic: Social Media

• How has social media re-kindled interest in SNA – what are the implications of having access to so much public data (re: how do organizations best leverage this information)?

• You’ve done some visualizations for this conference using the #CAT10 tag – what did the results show?

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Reference Materials

Additional Information

Reports• Social Media: Identity, Privacy, and Security Considerations• Social Media and FINRA: Twitter and LinkedIn Considerations• Social Media’s Cautionary Tale: A Management Overview• Field Research Study: Social Networking within the Enterprise• Field Research Study: Getting Started with Enterprise Social Networks• Field Research Study: Addressing Business and Cultural Needs• Field Research Study: Enabling Social Platforms• Field Research Study: Facilitating Social Participation• Field Research: Actions to Take on Enterprise Social Networking• Social Network Sites (reference architecture template)

Upcoming Research• From Twitter to Enterprise Micro-blogging• Enterprise Micro-blogging (reference architecture template)

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S o c i a l M e d I a R e s e a r c hF o u n d a t i o n

Open ToolsOpen DataOpen Scholarship

http://smrfoundation.org