The Power Of Words: Deconstructing Language Manipulation in Social Media Political Campaigns

This study investigates the strategic use of language in social media political campaigns, with particular emphasis on its impact on audience engagement and public discourse transformation. Through a comprehensive theoretical framework incorporating the Sapir-Whorf Hypothesis, Elaboration Likelihood Model, Critical Discourse Analysis, and Framing Theory, the research examines complex linguistic patterns, sentiment variations, and framing strategies across 10,000 campaign posts from major social media platforms. The study employs a mixed-methods approach, combining computational linguistics analysis with qualitative discourse examination. Using natural language processing tools and manual coding, researchers analyzed linguistic features including lexical choice, syntactic structures, metaphorical expressions, and rhetorical devices. Results reveal sophisticated patterns of deliberate linguistic manipulation designed to evoke specific emotional responses (72% of posts), reinforce political ideologies (65%), and adapt to temporal and platform-specific contexts (83%). The findings demonstrate that campaign language strategically evolves across different platforms, with Twitter showing more aggressive rhetoric (58%) compared to Facebook (31%) and Instagram (27%). Additionally, temporal analysis reveals significant shifts in linguistic strategies during critical campaign periods, with increased emotional language use during key political events (92% correlation). This research contributes to our understanding of digital political communication and offers practical insights for analyzing social media campaign strategies.

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Publication Details

Journal
International Journal of Multilingual Education and Applied Linguistics
Published
2025-02-21
DOI
https://doi.org/10.61132/ijmeal.v2i1.248
Citations
1
Primary Topic
Hate Speech and Cyberbullying Detection
Type
article
Field-Weighted Citation Impact
2.48
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article

The Power Of Words: Deconstructing Language Manipulation in Social Media Political Campaigns

Nurasia Natsir, Andi Suwarni, Nuraziza Aliah
1 citations
International Journal of Multilingual Education and Applied Linguistics
Hate Speech and Cyberbullying Detection
2.48
article

The Power Of Words: Deconstructing Language Manipulation in Social Media Political Campaigns

Nurasia Natsir, Andi Suwarni, Nuraziza Aliah
article en
1 citations

Abstract

This study investigates the strategic use of language in social media political campaigns, with particular emphasis on its impact on audience engagement and public discourse transformation. Through a comprehensive theoretical framework incorporating the Sapir-Whorf Hypothesis, Elaboration Likelihood Model, Critical Discourse Analysis, and Framing Theory, the research examines complex linguistic patterns, sentiment variations, and framing strategies across 10,000 campaign posts from major social media platforms. The study employs a mixed-methods approach, combining computational linguistics analysis with qualitative discourse examination. Using natural language processing tools and manual coding, researchers analyzed linguistic features including lexical choice, syntactic structures, metaphorical expressions, and rhetorical devices. Results reveal sophisticated patterns of deliberate linguistic manipulation designed to evoke specific emotional responses (72% of posts), reinforce political ideologies (65%), and adapt to temporal and platform-specific contexts (83%). The findings demonstrate that campaign language strategically evolves across different platforms, with Twitter showing more aggressive rhetoric (58%) compared to Facebook (31%) and Instagram (27%). Additionally, temporal analysis reveals significant shifts in linguistic strategies during critical campaign periods, with increased emotional language use during key political events (92% correlation). This research contributes to our understanding of digital political communication and offers practical insights for analyzing social media campaign strategies.

International Journal of Multilingual Education and Applied LinguisticsVol. 2(1)
NetApp (United States) (US), Indonesia Open University (ID)
Openalex Percentile: Top 10%
Hate Speech and Cyberbullying Detection
2.48
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