This paper presents an application of PageRank, a random-walk model originally devised for ranking Web search results, to ranking WordNet synsets in terms of how strongly they possess a given semantic property. The semantic properties we use for exemplifying the approach are positivity and negativity, two properties of central importance in sentiment analysis. The rationale of applying PageRank to detecting the semantic properties of synsets lies in the fact that the space of WordNet synsets may be seen as a graph, in which synsets are connectedthrough the binary relation

PageRanking WordNet Synsets: an application to opinion mining

Esuli A;Sebastiani F
2007

Abstract

This paper presents an application of PageRank, a random-walk model originally devised for ranking Web search results, to ranking WordNet synsets in terms of how strongly they possess a given semantic property. The semantic properties we use for exemplifying the approach are positivity and negativity, two properties of central importance in sentiment analysis. The rationale of applying PageRank to detecting the semantic properties of synsets lies in the fact that the space of WordNet synsets may be seen as a graph, in which synsets are connectedthrough the binary relation
2007
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Opinion mining
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/451093
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