Telligent Social Analytics Research & Tools Marc A. Smith Chief Social Scientist Telligent Systems
Page 2 (and more) is from people to people 2
Page 3 Patterns Patterns are left behind 3
Page 4 SOCIAL NETWORK THEORY 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
Page 5 Social media platforms are a source of multiple Social network data sets: “Friends” “Replies” “Follows” “Comments” “Reads” “Co-edits” “Co-mentions” “Hybrids”
Page 6 Journal of Social Structure: “Visualizing the Signatures of Social Roles in Online Discussion Groups” Distinguishing attributes: 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 Reply Magnet Ties from local isolates often inward only Sparse, few triangles Few intense ties
Page 7 Journal of Social Structure: “Visualizing the Signatures of Social Roles in Online Discussion Groups” Distinguishing attributes: Answer person Outward ties to local isolates Relative absence of triangles Few intense ties Discussion person Ties from local isolates often inward only Dense, many triangles Numerous intense ties Reply Magnet Ties from local isolates often inward only Sparse, few triangles Few intense ties
Page 8 Leading research: Adamic et al Knowledge Sharing and Yahoo Answers: Everyone Knows SomethingKnowledge Sharing and Yahoo Answers: Everyone Knows Something,Adamic, Lada A., Zhang Jun, Bakshy Eytan, and Ackerman Mark S., WWW2008, (2008)Adamic, Lada A.Zhang JunBakshy EytanAckerman Mark S.
Page 9 Use social network analysis measurements in reporting on social media data. Analytics calculates network metrics for all content authors. In-degree Out-degree Eigenvector centrality Clustering coefficient Ingredients of User Type Scores
Page 10 Social media usage generates Social Networks
Page 11 Display community members sorted by network attributes using Excel Data|Sort
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Page 13 User type reports in Telligent Analytics Include social network metrics to define different kinds of contributors: Answerer: users who reply to many questions from many people. Influencer: users who are connected to other well connected users. Asker: users who raise questions that get answered by answer people. Connector: highly connected users who are replied to or linked to by many other community users. Originator: initiates new content in the site that is often linked to by others. Commenter: replies or links to content created by others. Spectator: reads but tends not to create content. Overseer: moderates content created by others.
Page 14 NodeXL: Network Overview, Discovery and Exploration for Excel Leverage spreadsheet for storage of edge and vertex data
Page 15 The NodeXL Team
Page 16 The NodeXL project is Available via the CodePlexOpen Source Project Hosting Site: Site:
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Page 18 NodeXL: Display nodes with subgraph images sorted by network attributes using Excel Data|Sort
Page 19 Resources to support Educational Use of NodeXL Free Tutorial/Manual Data Sets Available
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Page 22 NodeXL: Filtered clusters
Page 23 NodeXL: Import social networks from
Page 24 NodeXL: Import social networks from
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Page 26 Social Network Analysis Engine Development: NodeXL Extend and apply social network analysis engine: Improve layouts and visualizations Additional metrics and measures Technical architecture shift to the web and cloud Scale and performance Clustering and time series analysis
Page 27 NodeXL Partnerships and community University of Maryland Ohio University Stanford University University of Pennsylvania YOU? 10,000 + downloads on Codeplex
Page 28 Telligent Analytics Provides a source of network edge lists and integrates social network metrics in User Type Scores Further possible social network analysis applications Recommendations: my friend’s edit what documents? Search optimization: show documents from “answer people” Role discovery: who are the topic starters? The answer people?
Page 29 Telligent Social Analytics Research & Tools Marc A. Smith Chief Social Scientist Telligent Systems