ESRC DTC PhD Student, Faculty of Social Sciences
Esmeralda Bon is a doctoral researcher in the School of Politics and International Relations at the University of Nottingham, where she is affiliated with the Centre for British Politics, NICEP and REPRESENT She holds a liberal arts and sciences BA (hons) in the Humanities and Rhetoric & Argumentation from University College Roosevelt and a MARes and MScRes from the University of Amsterdam, in Rhetoric, Argumentation Theory and Philosophy and Communication Science respectively, with political argumentation and political communication as specialisations. Her PhD is a collaborative studentship with the Committee on Standards in Public Life (CSPL) and mainly funded by the Economic and Social Research Council (ESRC) and the School of Politics and international Relations.
I am a graduating teaching assistant (GTA) for undergraduate modules on comparative politics and quantitative methods (Q-step):
As a CASE (collaborative) ESRC-funded full-time PhD candidate, I am working on the project "Public Opinion and Contemporary Communication Strategies in the UK". My research supervisors are Professor… read more
As a CASE (collaborative) ESRC-funded full-time PhD candidate, I am working on the project "Public Opinion and Contemporary Communication Strategies in the UK". My research supervisors are Professor Cees van der Eijk and Dr. Anja Neundorf.
I am primarily funded by the ESRC Doctoral Training Centre (in collaboration with the Committee on Standards in Public Life (CPSL)), the School of Politics and International Relations and Dr. Hendrik Muller's Vaderlandsch Fonds, as well as through a UK Data Service Impact Fellowship
I specialise in the study of political communication and political argumentation.
More broadly my substantive research interests include public opinion, election campaigns, (standards of) politician behaviour and populism and my methodological research interests include the application of rhetoric and argumentation (theory) and the interdisciplinary combined use of quantitative, qualitative and automated research methods to datasets of all sizes.
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