Multilingual Connotation Frames: A Case Study on Social Media for Targeted Sentiment Analysis and Forecast
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.
- Research Organization:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC05-76RL01830
- OSTI ID:
- 1373867
- Report Number(s):
- PNNL-SA-124156; 453040300
- 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
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