Multilingual Connotation Frames: A Case Study on Social Media for Targeted Sentiment Analysis and Forecast

Hannah Rashkin, Eric Bell, Yejin Choi, Svitlana Volkova


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
Bibkey:
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)
Copy Citation:
PDF:
https://preview.aclanthology.org/nschneid-patch-4/P17-2073.pdf