UNFOLDING THE POLITICAL PARANOID: A DISCOURSE-BASED INQUIRY INTO PAKISTANI POLITICAL NARRATIVES
PDF

Keywords

Political Ideology
Political language
Political narrative
Political reality and Power

How to Cite

Tehseem, T., Tassadiq, N., & Bokhari, Z. (2021). UNFOLDING THE POLITICAL PARANOID: A DISCOURSE-BASED INQUIRY INTO PAKISTANI POLITICAL NARRATIVES. Journal of Social Sciences and Humanities, 60(2), 57–72. https://doi.org/10.46568/jssh.v60i2.549
Share |

Abstract

This paper aims at unfolding political conspiracies that help to manipulate political reality in Pakistan. It significantly builds on the empirical data to show how language and social semeiotics are used to coin catchy slogans to serve the politicians. Political narratives remained a field of utmost interest to the discourse analysts since they offer a rich data for a significant use of persuasively manipulative language, and they signify one of the most implicit ways in which socio-political dogmas are disseminated so they are to be carefully crafted to help model linguistic choices. Based on Discourse Historical Approach (DHA) the present study highlights that the identifiable linguistic patterns perform a greater role in shaping political reality, and those are influenced by the sociopolitical and historical perspectives of the society concerned. The data comprises slogans from different registered political parties in Pakistan such as Pakistan People’s Party (PPP), Pakistan Muslim League Nawaz (PMLN) and Pakistan Tehreke’ Insaf (PTI). The study has found that the political parties in Pakistan use to craft new slogans to manipulate reality to legitimise political environment in their favour and in doing so, they use different semiotic resources including entities, socio-cultural circumstances and verbal exchanges.

https://doi.org/10.46568/jssh.v60i2.549
PDF
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Copyright (c) 2022 Tazanfal Tehseem, Naima Tassadiq, Zahra Bokhari

Metrics

Metrics Loading ...