Summary of the paper
| Title | Q-WordNet: Extracting Polarity from WordNet Senses |
|---|---|
| Authors | Rodrigo Agerri and Ana García-Serrano |
| Abstract | This paper presents Q-WordNet, a lexical resource consisting of WordNet sensesautomatically annotated by positive and negativepolarity. Polarity classification amounts to decide whether a text (sense,sentence, etc.) may be associated to positive or negativeconnotations. Polarity classification is becoming important within the fieldsof Opinion Mining and Sentiment Analysis for determiningopinions about commercial products, on companies reputation management, brandmonitoring, or to track attitudes by mining onlineforums, blogs, etc. Inspired by work on classification of word senses bypolarity (e.g., SentiWordNet), and taking WordNet as a startingpoint, we build Q-WordNet. Instead of applying external tools such assupervised classifiers to annotated WordNet synsets by polarity,we try to effectively maximize the linguistic information contained in WordNet,thereby taking advantage of the human effort put bylexicographers and annotators. The resulting resource is a subset of WordNetsenses classified as positive or negative. In this approach,neutral polarity is seen as the absence of positive or negative polarity. Theevaluation of Q-WordNet shows an improvement with respectto previous approaches. We believe that Q-WordNet can be used as a startingpoint for data-driven approaches in sentiment analysis. |
| Language | Semantics |
| Topics | Lexicon, lexical database, Emotion Recognition/Generation, Semantics |
Full paper  |
Q-WordNet: Extracting Polarity from WordNet Senses |
| Bibtex | @InProceedings{AGERRI10.695, author = {Rodrigo Agerri and Ana García-Serrano}, title = {Q-WordNet: Extracting Polarity from WordNet Senses}, 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} } |