Social impact retrieval: measuring author inﬂuence on information retrieval
Lanagan, James (2009) Social impact retrieval: measuring author inﬂuence on information retrieval. PhD thesis, Dublin City University.
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The increased presence of technologies collectively referred to as Web 2.0 mean the entire process of new media production and dissemination has moved away from an
authorcentric approach. Casual web users and browsers are increasingly able to play a more active role in the information creation process. This means that the traditional ways in which information sources may be validated and scored must adapt accordingly.
In this thesis we propose a new way in which to look at a user's contributions to the network in which they are present, using these interactions to provide a measure of
authority and centrality to the user. This measure is then used to attribute an query-independent interest score to each of the contributions the author makes, enabling us
to provide other users with relevant information which has been of greatest interest to a community of like-minded users. This is done through the development of two
algorithms; AuthorRank and MessageRank.
We present two real-world user experiments which focussed around multimedia annotation and browsing systems that we built; these systems were novel in themselves, bringing together video and text browsing, as well as free-text annotation. Using these systems as examples of real-world applications for our approaches, we then look at a
larger-scale experiment based on the author and citation networks of a ten year period of the ACM SIGIR conference on information retrieval between 1997-2007. We use the
citation context of SIGIR publications as a proxy for annotations, constructing large social networks between authors. Against these networks we show the eﬀectiveness of
incorporating user generated content, or annotations, to improve information retrieval.
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