Generating More-Positive and More-Negative Text

Diana Zaiu Inkpen, Ol'ga Feiguina, and Graeme Hirst

We present experiments on modifying the semantic orientation of the near-synonyms in a text. We analyze a text into an interlingual representation and a set of attitudinal nuances, with particular focus on its near-synonyms. Then we use our text generator to produce a text with the same meaning but changed semantic orientation (more positive or more negative) by replacing, wherever possible, words with near-synonyms that differ in their expressed attitude.

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