Conversation retrieval for microblogging sites

  • Authors:
  • Matteo Magnani;Danilo Montesi;Luca Rossi

  • Affiliations:
  • Department of Computer Science, Aarhus University, Aarhus-N, Denmark 8200;Department of Computer Science, University of Bologna, Bologna, Italy 40127;Department of Social Sciences, University of Urbino Carlo Bo, Urbino, Italy 61029

  • Venue:
  • Information Retrieval
  • Year:
  • 2012

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Abstract

In this article we introduce a novel search paradigm for microblogging sites resulting from the intersection of Information Retrieval and Social Network Analysis (SNA). This approach is based on a formal model of on-line conversations and a set of ranking measures including SNA centrality metrics, time-related conversational metrics and other specific features of current microblogging sites. The ranking approach has been compared to other methods and tested on two well known social network sites (Twitter and Friendfeed) showing that the inclusion of SNA metrics in the ranking function and the usage of a model of conversation can improve the results of search tasks.