User Behavior in Online Forums

1. User Behavior in Online Forums ECE697 Project Deepak Unnikrishnan

2. Overview • Online forums • Questions • Data Collection and Analysis • Results

3. Online Forums • Discussion sites in Internet • Mostly user generated content • Question-Answers • Opinions • Non-obvious relationships between participants • Limited information about users

4. Why analyze online forums ? • Questions • Do people participating in online forums form social bonds ? • Is the interaction network similar to that observed in OSNs (Facebook, Orkut, Blogs) ? • Interestingly, online forums are not well-researched

5. Related work • User Grouping Behavior in Online Forums, Shi et al., KDD 2009 (UMich, Microsoft Research) • Focus on user joining behavior in forum communities • Information diffusion • Recommendation of communities to users • Limited discussion on network properties

6. Data Set • Google Forums • http://www.google.com/support/forum/ • HTML Content – Easy to parse • Around 50 broad discussion topics • 900,000 discussion threads

7. Google Forums - Organization • Products (~50) • Discussion Categories (~5) • Threads (~1000s) • Posts (~100s)

8. Products

9. Discussion Categories

10. Threads

11. Posts

12. Top 10 Discussed Products • Account for 60% of total discussions

13. Data Set • Top 5 discussed products • Gmail • Youtube • Blogger • Adsense • Webmaster • ~400,000 threads • ~48,000 users

14. Evaluation Method • Crawl each product • Represent interactions in a discussion category as a directed graph • Visualize using SocNetV[1], Gephi[2] • Analyze data [1] http://socnetv.sourceforge.net/ [2] http://gephi.org/

15. Interaction Model A • A starts a thread • B, C reply to the thread • A replies to thread • Thickness -> Frequency of replies • Similar to Blog networks[1] B C [1]Communication Dynamics of Blog Networks, Goldberg et al., KDD’08

16. Visualization Topic - Adding adsense to a site

17. Visualization Experts • Node size ∞ Out-Degree Unanswered

18. Network Analysis

19. Participation in related discussions • Most users don’t participate in related discussions

20. Power-Law Node Degrees Gmail Youtube Blogger Adsense Outdegree Indegree

21. Power-Law Node Degrees – OSNs[1] [1]Measurement and analysis of online social networks, Mislove et al. IMC’07

22. Link degree correlations • 20%-40% overlap in top 10% of nodes • Overlap similar to the web than OSNs

23. Contribution to discussions • Users inclined towards contributing to discussions than initiating one. • Scope for recommendation systems – 3%-20% Unanswered posts

24. Reciprocity • Less than 1% of the total links are reciprocal • Higher reciprocity observed in larger forums

25. Clustering coefficient • Fairly sparse network – 7-14 times sparser than OSNs [1] Communication dynamics of blog networks, Goldberg et al. KDD’08 [2] The Small World Web, Adamic et al. ECDL’99 [3] Measurement and analysis of online social networks, Mislove et al. IMC’07

26. Density • Forums exhibit low density in network structure

27. Path length and Diameter

28. Conclusions • Similarities exist with OSNs • Users exhibit weak social bonds in online forums • Degrees obey power law • Sparse network structure with similarities to web and blog networks • Scope for recommendation systems • Recommending topic experts based on posts

29. Thank youQuestions ?