Imran Khan and Bilawal Bhutto’s Interviews on the CNN: A Multimodal Discourse Analysis

Authors

  • Hafiza Maria Anjum PhD Scholar, Department of Media and Communication Studies, International Islamic University Islamabad, Pakistan
  • Muhammad Riaz Khan Instructor, English Language Institute of the Jazan University Saudi Arabia
  • Dr. Muhammad Junaid Ghauri Lecturer, Department of Media and Communication Studies, International Islamic University Islamabad, Pakistan

DOI:

https://doi.org/10.35484/ahss.2023(4-I)08

Keywords:

Bilawal Bhutto, CNN, Imran Khan, Multimodal Discourse Analysis, Pakistan, Regime Change

Abstract

This research endeavor is an attempt to explore two Pakistani politicians’ (Imran Khan and Bilawal Bhutto) expressive mode of communication to propagate their narratives. Our overarching goal is to dissect the most consequential political discourses produced by the two politicians during their interviews with the CNN after a no confidence move against the then PM Imran Khan. We have employed the Multimodal Discourse Analysis (MMDA) to investigate the self- presentation modes and linguistics features used by the two leaders. Our findings show that during his interview with the CNN, Khan took care to maintain his composure, as evidenced by his posture and facial expressions, while the network painted Imran Khan as a political leader who will stop at nothing to restore his authority by casting blame on the United States. After analyzing the interviews of Imran Khan and Bilawal Bhutto, it is concluded that Imran Khan as a political leader is more mature than Bilawal Bhutto and has the ability to express his position clearly.

AHSS-Volume-4-issue-I-(January-to-March-2023)

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Published

2023-01-23

Details

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    PDF Downloads: 261

How to Cite

Anjum, H. M., Riaz Khan, M., & Junaid Ghauri, M. (2023). Imran Khan and Bilawal Bhutto’s Interviews on the CNN: A Multimodal Discourse Analysis. Annals of Human and Social Sciences, 4(1), 76–86. https://doi.org/10.35484/ahss.2023(4-I)08

Issue

Vol. 4 No. 1 (2023): January to March

Section

Articles

License

Open Access

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