With the rapid rise in the number of weblogs, or blogs, on the World Wide Web (WWW), there is a growing need to be able to quickly search for discussion on specific topics. While keyword searches using tools such as Google [4] or Technorati [18] can yield useful results, we run into the problem of having to enter contextualizing keywords to filter out unwanted and irrelevant search results. This has the unfortunate consequence of making the search process more complicated and possibly filtering out search hits that we would typically want. This paper outlines an approach to narrow search results to only relevant hits, while allowing for general keyword queries. Since the blogosphere constitutes a social network, the solution, BlogCrawler, attempts to use the properties of social networks to narrow the focus of search queries to only those blogs that the user is interested in. This paper presents an algorithm and empirical evaluation that exploits the social network implicit in blogs found on the WWW for the purpose of improving search on the Web.

Additional Metadata
Persistent URL dx.doi.org/10.1109/SocialCom.2010.102
Conference 2nd IEEE International Conference on Social Computing, SocialCom 2010, 2nd IEEE International Conference on Privacy, Security, Risk and Trust, PASSAT 2010
Citation
White, A, Chu, W. (Wayne), & Salehi-Abari, A. (Amirali). (2010). Media monitoring using social networks. In Proceedings - SocialCom 2010: 2nd IEEE International Conference on Social Computing, PASSAT 2010: 2nd IEEE International Conference on Privacy, Security, Risk and Trust (pp. 661–668). doi:10.1109/SocialCom.2010.102