Modeling Political Discourse with Sentence-BERT and BERTopic

TL;DR

This paper presents a novel framework combining BERTopic and Moral Foundations Theory to analyze the evolution and moral dimensions of political topics on Twitter during the 117th U.S. Congress, revealing insights into topic stability and moral framing.

Contribution

It introduces a scalable, interpretable method for tracking political topic shifts and moral influences over time on social media, integrating topic modeling with moral analysis.

Findings

Granular topics dissolve rapidly, limiting long-term influence.

Moral foundations like Care and Loyalty dominate durable topics.

Partisan differences influence moral framing strategies.

Abstract

Social media has reshaped political discourse, offering politicians a platform for direct engagement while reinforcing polarization and ideological divides. This study introduces a novel topic evolution framework that integrates BERTopic-based topic modeling with Moral Foundations Theory (MFT) to analyze the longevity and moral dimensions of political topics in Twitter activity during the 117th U.S. Congress. We propose a methodology for tracking dynamic topic shifts over time and measuring their association with moral values and quantifying topic persistence. Our findings reveal that while overarching themes remain stable, granular topics tend to dissolve rapidly, limiting their long-term influence. Moreover, moral foundations play a critical role in topic longevity, with Care and Loyalty dominating durable topics, while partisan differences manifest in distinct moral framing strategies. This work contributes to the field of social network analysis and computational political discourse by offering a scalable, interpretable approach to understanding moral-driven topic evolution on social media.