Summary of the paper

Title Happy Accident: A Sentiment Composition Lexicon for Opposing Polarity Phrases
Authors Svetlana Kiritchenko and Saif Mohammad
Abstract Sentiment composition is the determining of sentiment of a multi-word linguistic unit, such as a phrase or a sentence, based on its constituents. We focus on sentiment composition in phrases formed by at least one positive and at least one negative word ― phrases like 'happy accident' and 'best winter break'. We refer to such phrases as opposing polarity phrases. We manually annotate a collection of opposing polarity phrases and their constituent single words with real-valued sentiment intensity scores using a method known as Best―Worst Scaling. We show that the obtained annotations are consistent. We explore the entries in the lexicon for linguistic regularities that govern sentiment composition in opposing polarity phrases. Finally, we list the current and possible future applications of the lexicon.
Topics Opinion Mining / Sentiment Analysis, MultiWord Expressions & Collocations, Lexicon, Lexical Database
Full paper Happy Accident: A Sentiment Composition Lexicon for Opposing Polarity Phrases
Bibtex @InProceedings{KIRITCHENKO16.242,
  author = {Svetlana Kiritchenko and Saif Mohammad},
  title = {Happy Accident: A Sentiment Composition Lexicon for Opposing Polarity Phrases},
  booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)},
  year = {2016},
  month = {may},
  date = {23-28},
  location = {Portoro┼ż, Slovenia},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Sara Goggi and Marko Grobelnik and Bente Maegaard and Joseph Mariani and Helene Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  address = {Paris, France},
  isbn = {978-2-9517408-9-1},
  language = {english}
 }
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