PolarityRank: Finding an equilibrium between followers and contraries in a network

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In this paper we present the relevance ranking algorithm named PolarityRank. This algorithm is inspired in PageRank, the webpage relevance calculus method used by Google, and generalizes it to deal with graphs having not only positive but also negative weighted arcs. Besides the definition of our algorithm, this paper includes the algebraic justification, the convergence demonstration and an empirical study in which PolarityRank is applied to two unrelated tasks where a graph with positive and negative weights can be built: the calculation of word semantic orientation and instance selection from a learning dataset.

论文关键词:Ranking algorithms,Graphs,Relevance computing,Sentiment analysis,Data mining

论文评审过程:Received 13 May 2010, Revised 29 July 2011, Accepted 12 August 2011, Available online 7 September 2011.

论文官网地址:https://doi.org/10.1016/j.ipm.2011.08.003