"We Demand Justice!": Towards Social Context Grounding of Political Texts

ACL ARR 2024 April Submission612 Authors

Abstract:

Political discourse on social media often contains similar language used with opposing intended meanings. For example, the phrase \textit{thoughts and prayers}, is used to express sympathy for mass shooting victims, as well as satirically criticize the lack of legislative action on gun control. Fully understanding such discourse just by reading the text is difficult. However, knowledge of the social context information makes it easier.

We characterize the social context required to fully understand such ambiguous discourse, by grounding the text in real-world entities, actions, and attitudes. We propose two datasets that require an understanding of social context and benchmark them using large pre-trained language models, and several novel structured models. We show that structured models, explicitly modeling social context, outperform larger models on both tasks, but still lag significantly behind human performance. Finally, we perform an extensive analysis, to obtain further insights into the language understanding challenges posed by our social grounding tasks.

Paper Type: Long

Research Area: Computational Social Science and Cultural Analytics

Research Area Keywords: sociolinguistics, NLP tools for social analysis, quantitative analyses of news and/or social media

Contribution Types: Model analysis & interpretability, NLP engineering experiment, Data resources, Data analysis

Languages Studied: English

Submission Number: 612