Interpreting SentiWordNet for Opinion Classification
8195Authors
nan
Abstract
AbstractWe 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.
Keywords
Full Content
nan
Labeled Text
AbstractWe 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.
Publication Details
- Paper ID:
- 8195
- Year:
- 2010
- Publication:
- TIPSTER
- Publication Type:
- conf
- DOI:
- nan