Web 2.0 Mining: Analyzing Social Media

Authors: Anupam Joshi, Tim Finin, Akshay Java, Anubhav Kale, and Pranam Kolari

Book Title: Proceedings of the NSF Symposium on Next Generation of Data Mining and Cyber-Enabled Discovery for Innovation

Date: October 10, 2007

Abstract: Social media systems such as blogs, photo and link sharing sites, wikis and on-line forums are estimated to produce up to one third of new Web content. One thing that sets these ”Web 2.0” sites apart from traditional Web pages and resources is that they are intertwined with other forms of networked data. Their standard hyperlinks are enriched by social networks, comments, trackbacks, advertisements, tags, RDF data and metadata. We describe recent work on building systems that analyse these emerging social media systems to recognize spam blogs, find opinions on topics, identify communities of interest, derive trust relationships, and detect influential bloggers.

Type: InProceedings

Tags: social media, web 2.0

Google Scholar: pe3c2PBmgAUJ

Number of Google Scholar citations: 5 [show citations]

Number of downloads: 3236

Available for download as

size: 72440 bytes

Related Projects:

Past Project

 Semantic Discovery: Discovering Complex Relationships in Semantic Web.

Bookmark at: Digg | Del.icio.us | Connotea | CiteULike