Summary of the paper

Title Interpreting SentiWordNet for Opinion Classification
Authors Horacio Saggion and Adam Funk
Abstract We describe a set of tools, resources, and experiments for opinion classification in business-related datasources in two languages. In particular we concentrate on SentiWordNet text interpretation to produce word, sentence, and text-based sentiment features for opinion classification. We achieve good results in experiments using supervised learning machine over syntactic and sentiment-based features. We also show preliminary experiments where the use of summaries before opinion classification provides competitive advantage over the use of full documents.
Topics Document Classification, Text categorisation, Emotion Recognition/Generation, Lexicon, lexical database
Full paper Interpreting SentiWordNet for Opinion Classification
Slides -
Bibtex @InProceedings{SAGGION10.354,
  author = {Horacio Saggion and Adam Funk},
  title = {Interpreting SentiWordNet for Opinion Classification},
  booktitle = {Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)},
  year = {2010},
  month = {may},
  date = {19-21},
  address = {Valletta, Malta},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis and Mike Rosner and Daniel Tapias},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {2-9517408-6-7},
  language = {english}
Powered by ELDA © 2010 ELDA/ELRA