Principles, Models, and Methods for the Characterization and Analysis of Lurkers in Online Social Networks
Principles, models, and methods for the characterization and analysis of lurkers in online social networks Roberto Interdonato, Andrea Tagarelli DIMES Dept., Università della Calabria, Italy The 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining Lurking in OSNs: Principles, Models, and Methods Lurking in OSNs: Principles, Models, and Methods Lurk(er): what meanings Lurking in OSNs: Principles, Models, and Methods “Lurker”: let’s google it … Lurking in OSNs: Principles, Models, and Methods Lurk(er): what meanings Lurking in OSNs: Principles, Models, and Methods Outline 1. Lurking in online communities 2. Modeling lurking behaviors Topology-driven lurking definition The issue of controversial definitions Lurking and online behavioral 3. Lurker ranking methods models 4. Experimental evaluation The opportunity of de-lurking Static scenarios Dynamic scenarios 5. Applications to other domains Vicariously learning Lurking in social trust contexts 6. Delurking via Targeted Influence Maximization The DEvOTION algorithm 7. Conclusion and future work Lurking in OSNs: Principles, Models, and Methods LURKING IN ONLINE COMMUNITIES Lurking in OSNs: Principles, Models, and Methods The 1:9:90 rule of participation inequality (1/3) Arthur, C. (2006). What is the 1% rule? In: The guardian. UK: Guardian News and Media. Lurking in OSNs: Principles, Models, and Methods The 1:9:90 rule of participation inequality (2/3) • [Nonnecke & Preece, 2000] Email-based discussion lists: • 77 online health support groups and 21 online technical support groups • 46% of the health support group members and 82% of the technical support group members are lurkers • [Swartz, 2006] On Wikipedia: over 50% of all the edits are done by only 0.7% of the users • [van Mierlo, 2014] On four DHSNs (AlcoholHelpCenter, DepressionCenter, PanicCenter, and StopSmokingCenter): • 63,990 users, 578,349 posts • Lurkers account for 1.3% (n=4668), Contributors for 24.0% (n=88,732), and Superusers for 74.7% (n=276,034) of content Nonnecke, B., Preece, J.
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