| Using social network analysis to enhance information retrieval systems (2008) | |||||||||
Abstract | |||||||||
| It is an ongoing trend that people increasingly reveal very personal information on social network sites in particular and in the World Wide Web in general (Boyd & Ellison, 2007; Donath & Boyd, 2004; Hangwoo, 2006; Joinson, 2001; Ralph, Alessandro, & H. John Heinz, 2005). As this information becomes more and more publicly available from these various social network sites and the web in general, the social relationships between people can be discoverd and allows the automatic extraction of social networks. This trend is furthermore driven and enforced by recent initiatives such as facebooks connect , Myspaces data availability and Googles FriendConnect by making their social network data available to anyone. Furthermore the current development of the World Wide Web, termed as Web 2.0 by OReilly (O'Reilly, 2005), enables increasingly more people to publish information without profound technical knowledge. Blogs have gained a lot of attention in recent years. The whole blogosphere including more than 60 million blogs (Sifry, 2007) forms a reasonable body of information and knowledge. Additionally hypertext links made between blogs have been described as conversation, affiliation, or readership, implying a form of implicit social structure (Adamic & Adar, 2003; Flake, Lawrence, & Giles, 2000; Gibson, Kleinberg, & Raghavan, 1998; Herring et al., 2005; Kumar, Novak, Raghavan, & Tomkins, 2004; Marlow, 2006). That means that the publicly available information is increasingly annotated with author information which too allows the extraction of social networks. Although there is an increasing interest about social networks in general, there is little attention about the application of social network analysis to information retrieval systems. Recent studies (Borgatti & Foster, 2003; Cross, Borgatti, & Parker, 2001) suggest that the social network of a person has a significant impact on his or her information acquisition. Therefore the paper proposes the application of available social network data in the context of information retrieval systems. An outline of the research design for the exploration of meaningful sources for social network extraction and the impact of meaningful social network analysis methods and measures in the context of information retrieval systems will be given. The evaluation of these methods and measures is conducted on scientificcommons.org, a search platform for open access publications with 19 million publications and 7.9 million extracted authors and their co-author network. | |||||||||
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