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Exploring Populism in Texts: Leveraging AI for Substantive and Methodological Advancements

Project description

Understanding the populism phenomenon through text investigation

The rise of populism worldwide has prompted scholars to urgently study it. However, its adaptable nature makes defining it difficult, fuelling ongoing debates. This also poses challenges for empirical analyses centred on textual investigations. Despite progress in theoretical and empirical work, there is still a gap in our understanding of how to analyse populism through texts, from applying conceptual frameworks to adapting text-as-data techniques. Supported by the Marie Skłodowska-Curie Actions (MSCA) programme, the PopText project uses textual analysis to study the methodologies behind populism. It employs a robust methodology integrating manual coding and machine learning techniques. The project generates unique datasets capturing populism in texts, aiming to enhance our understanding of how it is conveyed across diverse temporal and contextual dimensions.

Objective

This interdisciplinary project embarks on an extensive exploration of the methodologies that underlie the study of populism through textual analysis, with the primary goal of enhancing our comprehension of this intricate phenomenon. The surge of populism on the global stage underscores an urgent need for scholarly investigation. However, the nuanced and adaptable nature of populism presents challenges, complicating efforts to establish a single, universally accepted definition. This conceptual ambiguity not only fuels ongoing debates about the core essence of populism but also permeates empirical analyses, including those centered on textual investigations. Despite the growing body of theoretical and empirical work, a noticeable gap persists in our grasp of the methodological subtleties inherent in the analysis of populism through texts. These methodological intricacies encompass a spectrum of dimensions, ranging from the application of conceptual frameworks to textual analyses, to the adaptation of text-as-data techniques capable of capturing the dynamic evolution of populism over time. This groundbreaking project marks an unprecedented endeavor in conducting cross-national and longitudinal evaluations of political parties' populist discourse. It employs a robust methodology integrating manual coding and machine learning techniques. By engaging with theoretical concepts and deploying cutting-edge AI tools to generate unique datasets capturing populism in texts, this project stands poised to enrich our nuanced understanding of how populism is conveyed across diverse temporal and contextual dimensions, pushing the boundaries of current knowledge in the field.

Fields of science (EuroSciVoc)

Keywords

Programme(s)

Topic(s)

Funding Scheme

HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

(opens in new window) HORIZON-MSCA-2023-PF-01

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Coordinator

UNIVERSITY COLLEGE DUBLIN, NATIONAL UNIVERSITY OF IRELAND, DUBLIN
Net EU contribution
€ 215 534,40
Address
BELFIELD
4 Dublin
Ireland
Region
Ireland Eastern and Midland Dublin
Activity type
Higher or Secondary Education Establishments
Links
Total cost
No data