Social Information Processing

1. 1010100100 1101 0010 00010111010011 010011011 01100001 11110 011 0101110011010 0111011010 001001 01111 00001001111010 011011010101 01001 01111 01100001001111010 100101111 00110 1001 10110101110100100 Social Information Processing March 26-28, 2008 AAAI Spring Symposium Stanford University

2. Definition • Social Information Processing is • an activity through which collective human actions organize knowledge • process which allows us to collectively solve problems far beyond any individual’s capabilities • a new information processing paradigm enabled by the Social Web AAAI Social Information Processing Symposium

3. The Social Web • The Social Web is a collection of technologies, practices and services that turn the Web into a platform for users to create and use content in a social context • Authoring tools blogs • Collaboration tools  wikis, Wikipedia • Tagging systems  del.icio.us, Flickr, CiteULike • Social networking  Facebook, MySpace, Essembly • Collaborative filtering  Digg, Amazon, Yahoo answers AAAI Social Information Processing Symposium

4. Social Web features • Users create content • Articles, opinions, creative products • Users annotate content • Metadata (e.g., tags) • Ratings • Users create connections • Between content and metadata • Between content or metadata and users • Among users (social networks) • Users interact • Discuss and rate content AAAI Social Information Processing Symposium

5. Social Web is interesting • Social Web as a complex dynamical system • Complex collective behavior emerges from actions taken by many users • Patterns emerge on large scale • Variety of interactions between users • Coordination, collaboration, conflict … • Network vs environment-mediated AAAI Social Information Processing Symposium

6. Social Web is interesting • Social Web as a knowledge-generating system • Users express personal knowledge (through articles, tags, links, …) or modify knowledge expressed by others • Tailor information to individual user … • Personalization and recommendation • … or combine users’ knowledge to create a knowledgebase • Wikipedia, wikis • folksonomy • FAQs, … AAAI Social Information Processing Symposium

7. Social Web is interesting • Social Web as a problem-solving system • By exposing human activity, Social Web allows users to harness the power of collective intelligence to solve problems • Manage the commons • Help the visually impaired get around in new places • Figure out who to trust AAAI Social Information Processing Symposium

8. Social Web is interesting • Lots of data for empirical studies • Large-scale experimenation • Social Web is amenable to analysis • Design systems for optimal performance AAAI Social Information Processing Symposium

9. Social Web is challenging • Social Web is enormous and growing rapidly • Some popular sites have >1 million users and >1 billion objects • 2G/day of “authored” content • 10-15G/day of user generated content[From Andrew Tomkins, Yahoo! Research] • Need new computational techniques to process massive data AAAI Social Information Processing Symposium

10. Social Web is challenging • Social Web is highly dynamic • New users and content • Links are created and destroyed • Need new computational approaches to deal with dynamic data AAAI Social Information Processing Symposium

11. Social Web is challenging • Social Web is highly heterogeneous • Variety of content and media types • Variety of information domains • Needs to be even more heterogeneous • Ability to express knowledge at different granularity levels • Micro-tagging: tag data within pages • Ability to express more complex knowledge • Specify relations: e.g., semantics of links • Need algorithms to combine heterogeneous data AAAI Social Information Processing Symposium

12. Social Web is challenging • Social Web is highly diverse • User participation has power law distribution • User expertise has power law distribution • Need approaches that go beyond ‘wisdom of crowds’ to combine knowledge from users • Averaging is not always the best solution • How do we best exploit diversity? • Understand incentives for user participation • Methods for improving content/metadata quality AAAI Social Information Processing Symposium

13. Schedule - Wednesday 9:00-9:15 Welcome 9:15-10:30am Invited talk Bernardo HubermanSocial Dynamics in the Age of the Web 10:30-11am Break 11-12:30pm Technical Session: Moderator Cosma Shalizi Ed ChiAugmented Social Cognition Tad HoggSolving the organizational free riding problem Riley CraneViral, Quality, and Junk Videos on YouTube 12:30-2pm - Lunch 3:30-4pm - Break 2-3:30pm Technical Session: Moderator Kristina Lerman Yi-Ching HuangYou Are What You Tag Julia StoyanovichLeveraging Tagging to Model User Interests in del.icio.us Steve WhittakerTemporal Tagging 4-5:30pm Technical Session: Moderator David Gutelius Georg GrohImplicit Social Network Construction in Web Portals Elizeu Santos-NetoContent Reuse and Interest Sharing Matt SmithSocial Capital in the Blogosphere: A Case Study 6-7pm – AAAI Reception AAAI Social Information Processing Symposium

14. Schedule - Thursday 9:00-10:30am Invited talk Brian Skyrms Signaling Games 10:30-11am Break 11-12:30pm Technical Session: Moderator Ed Chi John NicholsonThe Blind Leading the Blind Cosma ShaliziSocial Media as Windows on the Social Life of the Mind Luc SteelsSocial tagging in community memories 12:30-2pm - Lunch 2-3:30pm Technical Session: Moderator Tina Eliassi-Rad Aram GalstyanInfluence Propagation in Modular Networks Adam AnthonyGenerative Models for Clustering: The Next Generation Peter Pirolli A Probabilistic Model of Semantics 3:30-4pm - Break 4-5:30pm Technical Session: Moderator Tad Hogg Hak-Lae KimBuilding a Tag Sharing Service with the SCOT Ontology Yu Zhang Mining Target Marketing Groups From Users’Web of Trust Sihem Amer-Yahia Reviewing the Reviewers 5:45-7:30pm – AAAI Plenary Session AAAI Social Information Processing Symposium

15. Schedule - Friday 9-10:30am Technical Session: Moderator Chris Diehl Dennis WilkinsonMultiple Relationship Types in Online Communities and Social Networks Tina Eliassi-RadFinding Mixed-Memberships in Social Networks 10:30-11am - Break 11-12:30pm - Wrap up – Open to all AAAI Social Information Processing Symposium

16. Posters • John Nicholson Collaborative Route Information Sharing for the Visually Impaired • Tad Hogg and Gabor Szabo Diversity of Online Community Activities • Cosma Shalizi, Kristina Klinkner and Marcelo Camperi Measuring Shared Information and Coordinated Activity in a Network • Anon Plangprasopchok and Kristina Lerman On constructing shallow taxonomies from social annotations • Gustavo Glusman Users, photos, groups, words: analyzing mixed networks on flickr • Praveen Paritosh Freebase AAAI Social Information Processing Symposium

17. Thanks to • Organizing committee Kristina Lerman, David Gutelius, Bernardo Huberman, Srujana Merugu • Program committee Jim Blythe, Arindam Banerje, Sugato Basu, Jack Park, Scott Golder, Paolo Massa, Cosma Shalizi, Ed Chi, Tad Hogg, Chris Diehl, Sihem Amer-Yahia • Participants AAAI Social Information Processing Symposium