Modeling Framing in Immigration Discourse on Social Media

• URL: http://arxiv.org/abs/2104.06443v1
• Date: Tue, 13 Apr 2021 18:35:44 GMT
• Title: Modeling Framing in Immigration Discourse on Social Media
• Authors: Julia Mendelsohn, Ceren Budak, David Jurgens
• Abstract summary: framing of political issues can influence policy and public opinion. We create a new dataset of immigration-related tweets labeled for multiple framing typologies from political communication theory. We show how users' ideology and region impact framing choices, and how a message's framing influences audience responses.
• Score: 6.303801812707287
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The framing of political issues can influence policy and public opinion. Even though the public plays a key role in creating and spreading frames, little is known about how ordinary people on social media frame political issues. By creating a new dataset of immigration-related tweets labeled for multiple framing typologies from political communication theory, we develop supervised models to detect frames. We demonstrate how users' ideology and region impact framing choices, and how a message's framing influences audience responses. We find that the more commonly-used issue-generic frames obscure important ideological and regional patterns that are only revealed by immigration-specific frames. Furthermore, frames oriented towards human interests, culture, and politics are associated with higher user engagement. This large-scale analysis of a complex social and linguistic phenomenon contributes to both NLP and social science research.

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