An Aspect-Lexicon Creation and Evaluation Tool for Sentiment Analysis Researchers

نویسندگان

  • Mus'ab Husaini
  • Ahmet Koçyigit
  • Dilek Tapucu
  • Berrin A. Yanikoglu
  • Yücel Saygin
چکیده

In this demo paper, we present SARE, a modular and extendable semi-automatic system that 1) assists researchers in building gold-standard lexicons and evaluating their lexicon extraction algorithms; and 2) provides a general and extendable sentiment analysis environment to help researchers analyze the behavior and errors of a core sentiment analysis engine using a particular lexicon.

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تاریخ انتشار 2012