@inproceedings{rashkin-etal-2017-multilingual,
title = "Multilingual Connotation Frames: A Case Study on Social Media for Targeted Sentiment Analysis and Forecast",
author = "Rashkin, Hannah and
Bell, Eric and
Choi, Yejin and
Volkova, Svitlana",
editor = "Barzilay, Regina and
Kan, Min-Yen",
booktitle = "Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
month = jul,
year = "2017",
address = "Vancouver, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P17-2073",
doi = "10.18653/v1/P17-2073",
pages = "459--464",
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.",
}
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%0 Conference Proceedings
%T Multilingual Connotation Frames: A Case Study on Social Media for Targeted Sentiment Analysis and Forecast
%A Rashkin, Hannah
%A Bell, Eric
%A Choi, Yejin
%A Volkova, Svitlana
%Y Barzilay, Regina
%Y Kan, Min-Yen
%S Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
%D 2017
%8 July
%I Association for Computational Linguistics
%C Vancouver, Canada
%F rashkin-etal-2017-multilingual
%X 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.
%R 10.18653/v1/P17-2073
%U https://aclanthology.org/P17-2073
%U https://doi.org/10.18653/v1/P17-2073
%P 459-464
Markdown (Informal)
[Multilingual Connotation Frames: A Case Study on Social Media for Targeted Sentiment Analysis and Forecast](https://aclanthology.org/P17-2073) (Rashkin et al., ACL 2017)
ACL