Abstract
Product reviews are a corpus of textual data on consumer opinions. While reviews can be sorted by rating, there is limited support to search in the corpus for statements about particular topics, e.g. properties of a product. Moreover, where opinions are justified or criticised, statements in the corpus indicate arguments and counterarguments. Explicitly structuring these statements into arguments could help better understand customers' disposition towards a product. We present a semi-automated, rule-based information extraction tool to support the identification of statements and arguments in a corpus, using: argumentation schemes; user, domain, and sentiment terminology; and discourse indicators.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 31-42 |
| Number of pages | 12 |
| Journal | CEUR Workshop Proceedings |
| Volume | 925 |
| State | Published - 2012 |
| Externally published | Yes |
| Event | Workshop on Semantic Web and Information Extraction, SWAIE 2012 - Workshop in Conjunction with the 18th International Conference on Knowledge Engineering and Knowledge Management, EKAW 2012 - Galway, Ireland Duration: Oct 9 2012 → Oct 9 2012 |
Keywords
- Argumentation schemes
- Information extraction
- Product reviews
ASJC Scopus subject areas
- General Computer Science