Neuro-Linguistic Programming Analysis of Imran Khan's Political Discourse: A Study of his Speeches

Abstract

This work analyses the application of Neuro-Linguistic Programming (NLP) techniques in the political speeches of Imran Khan, a well-known politician in Pakistan. The goal of the study is to pinpoint and examine the ways in which Khan uses NLP techniques specifically, those derived from Milton Erickson's (1975) communication styles—to sway public opinion and affect audience behavior. The research attempts to comprehend the function of language in political communication by concentrating on the psychological framework of NLP, paying particular attention to how these tactics affect public opinion and involvement. Using AntConc software, the study's mixed-methods methodology combines quantitative and qualitative data analysis. Imran Khan's three most important speeches are chosen for the analysis based on their relevance, level of public engagement, and thematic coherence. The qualitative analysis focuses on identifying NLP patterns such as the Cause and Effect Model, Nominalization, Mind Reading, Lost Performatives, and Presupposition, which are crucial for understanding how language can be used to motivate and persuade audiences. The results demonstrate how well Khan uses these NLP strategies to connect with his audience and shape their opinion of him as a leader and political concerns. His language use is in line with NLP patterns that establish connection, arouse feelings, and shape listeners' views. The study comes to the conclusion that NLP methods may greatly improve political discourse, giving leaders the ability to interact with and sway public opinion. By providing insights into the ways in which linguistic techniques may be employed to fortify political power and mould public views, this research advances our knowledge of the link among language, natural language processing, and political discourse.