Abstract
People around the globe respond to major real world events through social media. To study targeted public sentiments across many languages and geographic locations, we introduce multilingual connotation frames: an extension from English connotation frames of Rashkin et al. (2016) with 10 additional European languages, focusing on the implied sentiments among event participants engaged in a frame. As a case study, we present large scale analysis on targeted public sentiments toward salient events and entities using 1.2 million multilingual connotation frames extracted from Twitter.- Anthology ID:
- P17-2073
- Volume:
- Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
- Month:
- July
- Year:
- 2017
- Address:
- Vancouver, Canada
- Editors:
- Regina Barzilay, Min-Yen Kan
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 459–464
- Language:
- URL:
- https://aclanthology.org/P17-2073
- DOI:
- 10.18653/v1/P17-2073
- Cite (ACL):
- Hannah Rashkin, Eric Bell, Yejin Choi, and Svitlana Volkova. 2017. Multilingual Connotation Frames: A Case Study on Social Media for Targeted Sentiment Analysis and Forecast. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 459–464, Vancouver, Canada. Association for Computational Linguistics.
- Cite (Informal):
- Multilingual Connotation Frames: A Case Study on Social Media for Targeted Sentiment Analysis and Forecast (Rashkin et al., ACL 2017)
- PDF:
- https://preview.aclanthology.org/fix-dup-bibkey/P17-2073.pdf