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

Hannah Rashkin, Eric Bell, Yejin Choi, Svitlana Volkova

[How to correct problems with metadata yourself]

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/teach-a-man-to-fish/P17-2073.pdf
PDF Search