DISCURSIVE STRATEGIES IN SELECTED 2019 PRESIDENTIAL CAMPAIGN SPEECHES

Authors

  • Chinonso Emmanuel Eze
  • Oluwasegun Matthew Amoniyan

Keywords:

Discourse, Discursive Strategies, Mental Model Theory, Campaign Speech

Abstract

Studies on discursive strategies have investigated multicultural business meetings, information seeking, social change, newspaper campaign advertisements, public dialogues, etc. but little or no scholarly examination has explored 2019 presidential campaign speeches. As a contribution to the previous studies on discursive strategies, the (present) work investigates the discursive strategies in selected 2019 presidential campaign speeches in Nigeria. The principal aim is to identify the discursive strategies employed by the contestants and the ideologies projected through the strategies identified. The study drew its data from the flag off campaign speeches of the contestants of the two major political parties: President Muhammadu Buhari of All Progressives Congress (APC) and Alhaji Atiku Abubakar of Peoples’ Democratic Party (PDP). Van Dijk’s mental model theory forms the theoretical framework for the study. Taking into consideration, the context model, situation model and experience model, Dijk’s mental model theory was adopted for the data analysis. The findings reveal that the contestants employed some linguistic constructions, such as rhetorical questions, parallel structures, and figurative expressions (metaphor) among others as discursive strategies in the campaign speeches. These strategies are equally found to be embodying some ideological projections which are discussed in this work using Dijk’s mental model theory. This study, therefore, will help the masses to understand more, the content of political campaign speeches and be able to act in accordance with the implicit meanings carried by the speeches.

Author Biographies

Chinonso Emmanuel Eze

Department of English and Literary Studies, University of Nigeria, Nsukka, Nigeria, 

Oluwasegun Matthew Amoniyan

 Department of Linguistics, University of Pittsburgh, USA. 

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Published

2022-09-01