Summary of the paper
| Title | Is Sentiment a Property of Synsets? Evaluating Resources for Sentiment Classification using Machine Learning |
|---|---|
| Authors | Aleksander Wawer |
| Abstract | Existing approaches to classifying documents by sentiment include machinelearning with features created from n-grams and part of speech. This paperexplores a different approach and examines performance of one selected machinelearning algorithm, Support Vector Machines, with features computed usingexisting lexical resources. Special attention has been paid to fine tuning ofthe algorithm regarding number of features. The immediate purpose of thisexperiment is to evaluate lexical and sentiment resources in document-levelsentiment classification task. Results described in the paper are also usefulto indicate how lexicon design, different language dimensions and semanticcategories contribute to document-level sentiment recognition. In a less directway (through the examination of evaluated resources), the experiment analyzesadequacy of lexemes, word senses and synsets as different possible layers forascribing sentiment, or as candidates for sentiment carriers. The proposedapproach of machine learning word category frequencies instead of n-grams andpart of speech features can potentially exhibit improvements in domainindependency, but this hypothesis has to be verified in future works. |
| Language | Lexicon, lexical database |
| Topics | Document Classification, Text categorisation, Emotion Recognition/Generation, Lexicon, lexical database |
Full paper  |
Is Sentiment a Property of Synsets? Evaluating Resources for Sentiment Classification using Machine Learning |
| Bibtex | @InProceedings{WAWER10.149, author = {Aleksander Wawer}, title = {Is Sentiment a Property of Synsets? Evaluating Resources for Sentiment Classification using Machine Learning}, 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} } |