Twitter Reactions to Shehbaz Sharif’s Speech: A Forensic Linguistic Examination of Political Discourse Online

This study presents the findings from a forensic linguistic analysis of social media comments responding to Shehbaz Sharif's speech. The analysis focused on linguistic features, emotional tones, and rhetorical strategies employed by users. The sentiment analysis revealed that the majority of comments were emotionally charged and sharply critical of the political leader, with frequent use of pejorative terms like "chor" (thief) and "dramaybaaz" (drama actor), reflecting political disillusionment and social frustration. Sarcasm and ridicule were commonly employed, often veiled in courteous or mocking language, suggesting an underlying intention of disapproval. Additionally, code-switching between Roman Urdu, Urdu, and English was strategically used to emphasize points, intensify emotions, and engage a broader audience. The posts also revealed strong political polarization, with users showing loyalty to opposition parties and using divisive language. Some comments bordered on legally sensitive issues, such as hate speech and defamation, highlighting the relevance of forensic linguistics in identifying online threats. This research underscores the complex nature of social media discourse, which not only conveys political opinion but also reflects power dynamics, ideological divides, and societal tensions.

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Social science review archives.
Published
2025-09-20
DOI
https://doi.org/10.70670/sra.v3i3.1059
Primary Topic
Hate Speech and Cyberbullying Detection
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article
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article

Twitter Reactions to Shehbaz Sharif’s Speech: A Forensic Linguistic Examination of Political Discourse Online

Svati H. Shah, M. Alamgir, Ijaz ul Haq
Social science review archives.
Hate Speech and Cyberbullying Detection
article

Twitter Reactions to Shehbaz Sharif’s Speech: A Forensic Linguistic Examination of Political Discourse Online

Svati H. Shah, M. Alamgir, Ijaz ul Haq
article en

Abstract

This study presents the findings from a forensic linguistic analysis of social media comments responding to Shehbaz Sharif's speech. The analysis focused on linguistic features, emotional tones, and rhetorical strategies employed by users. The sentiment analysis revealed that the majority of comments were emotionally charged and sharply critical of the political leader, with frequent use of pejorative terms like "chor" (thief) and "dramaybaaz" (drama actor), reflecting political disillusionment and social frustration. Sarcasm and ridicule were commonly employed, often veiled in courteous or mocking language, suggesting an underlying intention of disapproval. Additionally, code-switching between Roman Urdu, Urdu, and English was strategically used to emphasize points, intensify emotions, and engage a broader audience. The posts also revealed strong political polarization, with users showing loyalty to opposition parties and using divisive language. Some comments bordered on legally sensitive issues, such as hate speech and defamation, highlighting the relevance of forensic linguistics in identifying online threats. This research underscores the complex nature of social media discourse, which not only conveys political opinion but also reflects power dynamics, ideological divides, and societal tensions.

Social science review archives.Vol. 3(3)
Kohat University of Science and Technology (PK), Riphah International University (PK)
Openalex Percentile: Top 86%
Hate Speech and Cyberbullying Detection
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Twitter Reactions to Shehbaz Sharif’s Speech: A Forensic Linguistic Examination of Political Discourse Online — Svati H. Shah, M. Alamgir, et al. · Social science review archives. (2025) | TGRS Research Map | TGRS