Exploring the Use of Linguistic Features in Sentiment Analysis

نویسندگان

  • Michel Généreux
  • Marina Santini
چکیده

In this paper we describe some explorations of the potential of genre-revealing features on automatic sentiment analysis. In particular, we use a small subset of the ‘linguistic facets’ employed in recent experiments on automatic genre identification in combination with more traditional sentiment-revealing features on two different single-genre corpora: a corpus of English blogs and a corpus of French reviews (relectures). Although still preliminary, results show that linguistic facets might have a positive influence on sentiment analysis because 6 out of 14 facets used in the experiments are among the first 22 most important discriminative features.

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تاریخ انتشار 2007