The Towards a Social Science of Web 2.0 is taking place at the University of York, organized by the Social Informatics Research Unit. Here come my notes.
Keynote Speech: Bernie Hogan
Capturing Online Social Networks: Techniques, Insights and Challenges
Network Analysis
Importance of network analysis. How to tell who’s the most connected, who’s connected to who and how
- Degree: number of links
- Betweenness: shortest paths
- PageRank: links to high degree
- Positions: blockmodelling
Networks can be made up of subgroups/subnetworks, even multiple spare networks somehow connected one to each other by a common node that just bridges them.
Personal Networks
- Comparative
- For sampling large networks
- Often regression-based
- Visualizations of networks rarely show person
Network Analysis Tools
- Scraping: Python, Perl, PHP, Java (JUNG)
- Cleaning: same as before + databases
- Analyzing: UClnet, Pajek, JUNG, Egotistics
- Visualizing: NetDraw, Pajek, Guess
- http://www.insna.org
Social Bookmarking
Social news: people will filter news for each other. Slashdot, reddit, Digg. Based on collaborative work/research and ways of voting the news/user.
Distribution of stories made popular in Digg: power curve, but really steep.
Limits of Social Networks
- What’s a friend?
- Multiplexity
- Time
- Convenience
- Entity resolution
Comments from the audience
This social networks are kind of a popularity contest
- Where’s the threshold that separates being in the network and being outside of it (in terms of traffic, contributions, etc.)? Ain’t we, in some way, acknowledging… trashholding and not real participation in the network?
More Info
- Hogan, B. (2007) Using Information Networks to Study Social Behavior. In IEEE Data Engineering Bulletin. 30(2). Pp.6-14
- Hogan, B. (forthcoming) Analyzing Social Networks Via the Internet. In Fielding, N., Lee, R. and Blank, G. Sage Handbook of Online Research Methods
- Egotistic, via Knowbie’s Weblog, by Maria Chiara Pettenati
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