www 2009 Madrid

General CFP
| Data Mining | Industrial Practice and Experience | Internet Monetization |
Performance, Scalability and Availability | Rich Media | Search | Security and Privacy |
| Semantic / Data Web | Social Networks and Web 2.0 | User Interfaces and Mobile Web |
|Web Engineering | WWW in Ibero-America | XML and Web Data |

| Developers Track | Panels | Posters | Tutorials | Workshops |


Social Networks and Web 2.0

Today a second generation of web-based communities and hosted services - such as social networking sites, wikis and folksonomies - account for a significant portion of web traffic and content generation. The term Web 2.0 has been coined to embrace such collaborative applications and also to indicate a "social" approach to generating and distributing Web content, characterized by open communication, decentralization of authority, and freedom to share and re-use. Implicit and explicit in many Web 2.0 applications are social networks, through which users share and filter content, collaborate, seek information, and interact socially on the Web.

The Web 2.0 and Social Network Track provides a unique forum both for describing innovative collaborative and open applications, and data sharing scenarios, as well as novel technologies and methodologies for building and managing these applications. We welcome contributions relating to specific classes of applications as well as to cross-cutting issues. Relevant topics include, but are not restricted to, the following:

  • E-Communities and Web-based collaboration
  • Ethnographic and data mining* analysis of online communities including blogs, online social networking and social media sites, and tagging systems
  • Temporal and community evolution of Wikipedia and other open collaborative efforts
  • Social network analysis of online environments, including community discovery and structure
  • Social reputation and recommendation systems, trust management
  • Collaborative filtering and content ranking using social media
  • Data management in collaborative open applications
  • Assured data sharing and integration of access control policies
  • Data sharing incentives and risks
  • Metadata and annotation management
  • Intellectual property and DRM in Web 2.0 applications
  • Data and workflow provenance across Web 2.0 applications
  • Web standards for collaborative applications
  • Experience reports and case studies for collaborative open applications.

Papers whose main contribution is the development of novel data mining techniques, as opposed to applications to the social networks and Web 2.0 domain, should be submitted to the data mining track.

Paper formatting requirements are provided on the Submission page.

Track chairs

  • Lada Adamic, University of Michigan, USA
  • Vladimir Soroka, IBM Research, Israel

Program Committee

  • Mark Ackerman (University of Michigan, USA)
  • Helen Ashman (University of South Australia, Australia)
  • Rafae Bhatti (IBM Almaden, USA)
  • Athman Bouguettaya (Virginia Tech, USA)
  • Ciro Cattuto (ISI Foundation, Italy)
  • Nosh Contractor (Northwestern University, USA)
  • Scott Counts (Microsoft Research, USA)
  • Jon Crowcroft (University of Cambridge, UK)
  • Nathan Eagle (Santa Fe Institute, USA)
  • Shel Finkelstein (SAP Labs, USA)
  • Danyel Fisher (Microsoft, USA)
  • Jill Freyne (UCD, Dublin, Ireland)
  • Lise Getoor (University of Maryland, USA)
  • Werner Geyer (IBM Research, USA)
  • C. Lee Giles (Pennsylvania State University, USA)
  • Natalie Glance (Google, USA)
  • Scott Golder (Cornell, USA)
  • Ido Guy (IBM Research, Israel)
  • Susan Herring (Indiana University, USA)
  • Matthew Hurst (Microsoft Live Labs, USA)
  • Michal Jacovi (IBM Research, Israel)
  • Matthias Jarke (RWTH Aachen, Germany)
  • Akshay Java (University of Maryland-Baltimore County, USA)
  • Ajita John (Avaya Labs, USA)
  • Lalana Kagal (MIT, USA)
  • David Kempe (University of Southern California, USA)
  • Pranam Kollari (Yahoo! Applied Research, USA)
  • Gueorgi Kossinets (Cornell University, USA)
  • Tessa Lau (IBM Research, USA)
  • Kristina Lerman (USC, ISI, USA)
  • Gili Leshed (Cornell University, USA)
  • Jure Leskovec (Cornell University)
  • David Liben-Nowell (Carleton College, USA)
  • Vittorio Loretto (University of Rome, Italy)
  • Cameron Marlow (Facebook, USA)
  • Yutaka Matsuo (National Institute of AIST, Japan)
  • Massimo Mecella (University of Rome "La Sapienza", Italy)
  • Filippo Menczer (Indiana University, USA)
  • Bijan Parsia (University of Manchester, UK)
  • Adam Perer (University of Maryland, USA)
  • Anabel Quan Haase (University of Western Ontario, Canada)
  • Sheizaf Rafaeli (Haifa University, Israel)
  • Gilad Ravid (Ben-Gurion University, Israel)
  • John Riedl (University of Minnesota, USA)
  • Rahul Sami (University of Michigan, USA)
  • Barry Smyth (University College, Dublin, Ireland)
  • Eyal Sonsino (Google, Israel)
  • Ellen Spertus (Google Inc., USA)
  • Anna Cinzia Squicciarini (Purdue University, USA)
  • Kien-Lee Tan (National University of Singapore, Singapore)
  • Milan Vojnovic (Microsoft Research, UK)
  • Chris Volinsky (AT&T Labs-Research, USA)
  • Dennis Wilkinson (HP Labs, USA)
  • Volker Wulf (Fraunhofer, Germany)
  • Haizheng Zhang (Microsoft Live, USA)
  • Jun Zhang (Pitney Bowes, USA)
  • Aoying Zhou (Fudan University, China)