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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Leveraging Microblogs for Resource Ranking
verfasst von : Tomáš Majer, Marián Šimko
Erschienen in: SOFSEM 2012: Theory and Practice of Computer Science
Verlag: Springer Berlin Heidelberg
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In order to compute page rankings, search algorithms primarily utilize information related to page content and link structure. Microblog as a phenomenon of today provides additional, potentially relevant, information – short messages often containing hypertext links to web resources. Such source is particularly valuable when considering a temporal aspect of information, which is being published every second. In this paper we present a method for resource ranking based on Twitter data structure processing. We apply various graph algorithms leveraging the notion of a node centrality in order to deduce microblog-based resource ranking. Our method ranks a microblog user based on his followers count with respect to a number of (re)posts and reflects it into resource ranking. The evaluation of the method showed that micro-based resource ranking
a
) can not be substituted by a common form of an explicit user rating, and
b
) has the great potential for search improvement.