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- W80336435 abstract "Many approaches to sentiment analysis rely on lexica where words are tagged with their prior polarity - i.e. if a word out of context evokes something positive or something negative. In particular, broad-coverage resources like SentiWordNet provide polarities for (almost) every word. Since words can have multiple senses, we address the problem of how to compute the prior polarity of a word starting from the polarity of each sense and returning its polarity strength as an index between -1 and 1. We compare 14 such formulae that appear in the literature, and assess which one best approximates the human judgement of prior polarities, with both regression and classification models." @default.
- W80336435 created "2016-06-24" @default.
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- W80336435 date "2012-12-18" @default.
- W80336435 modified "2023-09-25" @default.
- W80336435 title "Assessing Sentiment Strength in Words Prior Polarities" @default.
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