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Exploring the Emotional Landscape of the Montenegro Presidential Election

A Sentiment and Thematic Analysis

Bibliographic Data

ID22326953
AuthorsIgor Ivanovic (0000-0002-7372-104X, University of Montenegro, corresponding author)
Year2025
Issue50
Publication date2025-04-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFolia linguistica et litteraria (JOURNAL)
Journal identifiersISSN: 1800-8542 • E-ISSN: 2337-0955
PublisherFaculty of Philology - University of Montenegro (PUBLISHER)
DOI10.31902/fll.50.2024.11
OpenAlexW4410126107
LanguageEN
References cited7

This paper presents an empirical analysis of the sentiment dynamics surrounding the 2023 presidential election in Montenegro, employing the VADER sentiment analysis tool to scrutinise text data from various media sources, including social media platforms such as Twitter, Facebook, and Instagram, over three distinct phases: pre-election, election day, and postelection, with validation using perplexity and coherence measures. The study systematically quantifies shifts in public sentiment, demonstrating how these fluctuations correlate with key electoral events. Pre-election analysis revealed a cautiously optimistic sentiment, with a slight predominance of positive over negative sentiments. On election day, sentiment polarised significantly, evidenced by increased negative and positive sentiments, reflecting heightened public engagement and anxiety. Post-election sentiment saw a marked decline in negativity and a rise in neutrality, suggesting a societal shift towards acceptance and reflection following the electoral outcome. This paper elucidates the complex emotional landscape of electoral processes and discusses the implications of these sentiment shifts in understanding democratic transitions. The findings highlight the potent role of public sentiment as both a reflection of and a response to political developments, offering insights into the broader socio-political repercussions of elections. Future research could extend these analyses to other electoral contexts to further refine our understanding of sentiment dynamics as predictors of political and social change

Cartography · Geography · Montenegro · Political science · Politics · Presidential election · Presidential system · Qualitative research · Regional science · Sentiment analysis · Social science · Sociology · Thematic analysis · Thematic map · Computer Science · Emotions and Moral Behavior · Law · Military History and Strategy · Populism, Right-Wing Movements · Artificial Intelligence

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Highly citedNo

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