Sentiment Polarity Shifts in News Headlines Before and After Elections: A Cross-National Corpus-Based Analysis of Political Media Discourse

Durdana Parveen

doi:10.5281/zenodo.21726069

Authors

Durdana Parveen Research Institute for Digital and Social Transformation Studies, Karachi, Pakistan https://orcid.org/0009-0001-1210-9519

DOI:

https://doi.org/10.5281/zenodo.21726069

Keywords:

sentiment analysis, news headlines, elections, corpus linguistics, sentiment polarity, VADER, political communication, framing

Abstract

This study investigates shifts in sentiment polarity in news headlines surrounding major electoral events, focusing on the 2019 UK General Election, the 2020 US Presidential Election, and the 2022 Pakistani General Election. Situated at the intersection of corpus linguistics, critical discourse analysis, and political communication, the research examines how electoral outcomes influence the emotional and evaluative tone of media discourse. Drawing on corpus-based sentiment analysis (Liu, 2012; Taboada, 2016), Fairclough’s (2003) critical discourse analytical framework, and framing theory (Entman, 1993), the study analyzes a corpus of approximately 180,000 news headlines collected from leading online newspapers in the United Kingdom, the United States, and Pakistan. The dataset covers a sixty-day period surrounding each election, comprising a thirty-day pre-election phase and a thirty-day post-election phase. Sentiment polarity was measured using the VADER sentiment lexicon, while a manually coded 10% subsample was employed to validate the automated classifications and ensure analytical reliability. The findings reveal statistically significant changes in headline sentiment following election outcomes across all three national contexts. Media outlets perceived to be aligned with victorious political parties exhibited notable increases in positive sentiment, whereas outlets associated with defeated parties demonstrated declines in sentiment polarity and heightened negativity. Comparative analysis further indicates that American news media displayed the highest degree of sentiment fluctuation, reflecting a deeply polarized political environment, while Pakistani newspapers recorded the most negative sentiment baseline during the pre-election period. These findings suggest that news headlines function as affective indicators of political alignment and ideological positioning. The study contributes to methodological developments in corpus-assisted media analysis and advances understanding of the relationship between electoral outcomes, media framing, and public discourse.

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