Opinion Retrieval Systems using Tweet-external Factors

Yoon-Sung Kim, Young-In Song, Hae-Chang Rim


Abstract
Opinion mining is a natural language processing technique which extracts subjective information from natural language text. To estimate an opinion about a query in large data collection, an opinion retrieval system that retrieves subjective and relevant information about the query can be useful. We present an opinion retrieval system that retrieves subjective and query-relevant tweets from Twitter, which is a useful source of obtaining real-time opinions. Our system outperforms previous opinion retrieval systems, and it further provides subjective information about Twitter authors and hashtags to describe their subjective tendencies.
Anthology ID:
C16-2027
Volume:
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations
Month:
December
Year:
2016
Address:
Osaka, Japan
Venue:
COLING
SIG:
Publisher:
The COLING 2016 Organizing Committee
Note:
Pages:
126–130
Language:
URL:
https://aclanthology.org/C16-2027
DOI:
Bibkey:
Cite (ACL):
Yoon-Sung Kim, Young-In Song, and Hae-Chang Rim. 2016. Opinion Retrieval Systems using Tweet-external Factors. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations, pages 126–130, Osaka, Japan. The COLING 2016 Organizing Committee.
Cite (Informal):
Opinion Retrieval Systems using Tweet-external Factors (Kim et al., COLING 2016)
Copy Citation:
PDF:
https://preview.aclanthology.org/author-url/C16-2027.pdf