PageRanking WordNet Synsets: an application to opinion mining

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 "a term belonging to synset sk occurs in the gloss of synset si", and on the hypothesis that this relation may be viewed as a transmitter of such semantic properties. The data for this relation can be obtained from eXtended WordNet, a publicly available sensedisambiguated version of WordNet. We argue that this relation is structurally akin to the relation between hyperlinkedWeb pages, and thus lends itself to PageRank analysis. We report experimental results supporting our intuitions.