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 foropinion 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 oversyntactic and sentiment-based features. We also show preliminary experimentswhere the use of summaries before opinion classification provides competitiveadvantage over the use of full documents. |
| Language | Lexicon, lexical database |
| Topics | Document Classification, Text categorisation, Emotion Recognition/Generation, Lexicon, lexical database |
Full paper  |
Interpreting SentiWordNet for Opinion Classification |
| Bibtex | @InProceedings{SAGGION10.354, author = {Horacio Saggion and Adam Funk}, title = {Interpreting SentiWordNet for Opinion Classification}, booktitle = {Proceedings of the Seventh conference on International Language Resources and Evaluation (LREC'10)}, year = {2010}, month = {may}, date = {19-21}, address = {Valletta, Malta}, editor = {Nicoletta Calzolari (Conference Chair), Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odjik, Stelios Piperidis, Mike Rosner, Daniel Tapias}, publisher = {European Language Resources Association (ELRA)}, isbn = {2-9517408-6-7}, language = {english} } |