Sentiment and/or Figurative Language Analysis in Social Media

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The project is aimed at the automatic classification of sentiment in texts on Twitter or other social media, tentatively addressing issues involving negation and/or figurative language, that is, language which intentionally conveys secondary or extended meanings (such as sarcasm, irony and metaphor). Figurative language creates a significant challenge for sentiment analysis systems, as direct approaches based on words and their lexical semantics often are inadequate in the face of indirect meanings. A subgoal of the project would then be to find a set of tweets rich in figurative language, but the main goal would be to determine whether the writer of such tweets has expressed a positive or negative sentiment (commonly displaying positive or negative emotions towards a product, person, political party, etc.), and possibly the degree to which this sentiment has been communicated.