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

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 using 1.2 million multilingual connotation frames extracted from Twitter. We rely on connotation frames to build models to forecast country-specific connotation dynamics – perspective change over time towards salient entities and events. Our results demonstrate that connotation dynamics can be accurately predicted up to half a week in advance.

Authors:
; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1373867
Report Number(s):
PNNL-SA-124156
453040300
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Conference
Resource Relation:
Conference: The 55th Annual Meeting of the Association for Computational Linguistics, July 30-August 4, 2017, Vancouver, BC, Canada, 2:459-464; Paper No. P17-2073
Country of Publication:
United States
Language:
English
Subject:
connotation frames; sentiment analysis; deep learning; forecasting; multilingual

Citation Formats

Rashkin, Hannah J., Bell, Eric B., Choi, Yejin, and Volkova, Svitlana. Multilingual Connotation Frames: A Case Study on Social Media for Targeted Sentiment Analysis and Forecast. United States: N. p., 2017. Web. doi:10.18653/v1/P17-2073.
Rashkin, Hannah J., Bell, Eric B., Choi, Yejin, & Volkova, Svitlana. Multilingual Connotation Frames: A Case Study on Social Media for Targeted Sentiment Analysis and Forecast. United States. doi:10.18653/v1/P17-2073.
Rashkin, Hannah J., Bell, Eric B., Choi, Yejin, and Volkova, Svitlana. Sun . "Multilingual Connotation Frames: A Case Study on Social Media for Targeted Sentiment Analysis and Forecast". United States. doi:10.18653/v1/P17-2073.
@article{osti_1373867,
title = {Multilingual Connotation Frames: A Case Study on Social Media for Targeted Sentiment Analysis and Forecast},
author = {Rashkin, Hannah J. and Bell, Eric B. and Choi, Yejin and Volkova, Svitlana},
abstractNote = {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 using 1.2 million multilingual connotation frames extracted from Twitter. We rely on connotation frames to build models to forecast country-specific connotation dynamics – perspective change over time towards salient entities and events. Our results demonstrate that connotation dynamics can be accurately predicted up to half a week in advance.},
doi = {10.18653/v1/P17-2073},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sun Jul 30 00:00:00 EDT 2017},
month = {Sun Jul 30 00:00:00 EDT 2017}
}

Conference:
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