Summary of the paper
| Title | Multilingual Corpus Development for Opinion Mining |
|---|---|
| Authors | Julia Maria Schulz, Christa Womser-Hacker and Thomas Mandl |
| Abstract | Opinion Mining is a discipline that has attracted some attention lately. Mostof the research in this field has been done for English or Asian languages,due to the lack of resources in other languages. In this paper we describe anapproach of building a manually annotated multilingual corpus for the domain ofproduct reviews, which can be used as a basis for fine-grained opinionanalysis also considering direct and indirect opinion targets. For eachsentence in a review, the mentioned product features with their respectiveopinion polarity and strength on a scale from 0 to 3 are labelled manually bytwo annotators. The languages represented in the corpus are English, Germanand Spanish and the corpus consists of about 500 product reviews per language.After a short introduction and a description of related work, we illustrate theannotation process, including a description of the annotation methodology andthe developed tool for the annotation process. Then first results on theinter-annotator agreement for opinions and product features are presented. Weconclude the paper with an outlook on future work. |
| Language | Emotion Recognition/Generation |
| Topics | Corpus (creation, annotation, etc.), Multilinguality, Emotion Recognition/Generation |
Full paper  |
Multilingual Corpus Development for Opinion Mining |
| Bibtex | @InProceedings{SCHULZ10.689, author = {Julia Maria Schulz, Christa Womser-Hacker and Thomas Mandl}, title = {Multilingual Corpus Development for Opinion Mining}, 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} } |