Summary of the paper

Title ANEW+: Automatic Expansion and Validation of Affective Norms of Words Lexicons in Multiple Languages
Authors Samira Shaikh, Kit Cho, Tomek Strzalkowski, Laurie Feldman, John Lien, Ting Liu and George Aaron Broadwell
Abstract In this article we describe our method of automatically expanding an existing lexicon of words with affective valence scores. The automatic expansion process was done in English. In addition, we describe our procedure for automatically creating lexicons in languages where such resources may not previously exist. The foreign languages we discuss in this paper are Spanish, Russian and Farsi. We also describe the procedures to systematically validate our newly created resources. The main contributions of this work are: 1) A general method for expansion and creation of lexicons with scores of words on psychological constructs such as valence, arousal or dominance; and 2) a procedure for ensuring validity of the newly constructed resources.
Topics Validation of LRs, Opinion Mining / Sentiment Analysis, Lexicon, Lexical Database
Full paper ANEW+: Automatic Expansion and Validation of Affective Norms of Words Lexicons in Multiple Languages
Bibtex @InProceedings{SHAIKH16.79,
  author = {Samira Shaikh and Kit Cho and Tomek Strzalkowski and Laurie Feldman and John Lien and Ting Liu and George Aaron Broadwell},
  title = {ANEW+: Automatic Expansion and Validation of Affective Norms of Words Lexicons in Multiple Languages},
  booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)},
  year = {2016},
  month = {may},
  date = {23-28},
  location = {Portorož, 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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