One of the main challenges in comparative studies on populism concerns its temporal and spatial measurements within and between many parties and countries. Significant and ground-breaking contributions in this area have emerged in recent years. We all know that the topic of populism is complex to analyse empirically because of many intrinsic characteristics, such as the difficulty of defining it unambiguously, grasping its nuances or context-specificity. However, textual analysis has proved helpful for these purposes, and automated methods can further improve research in this direction. During the seminar, we will introduce and deepen the debate on populism, with particular reference to the textual and text-as-data approaches. We will analyse key concepts and introduce different text-based methods used to measure this phenomenon, new computational techniques and machine learning, among the others. We will discuss the advantages and disadvantages of adopting text-based approaches and stimulate a critical and constructive discussion on this complex and divisive concept.
Jessica Di Cocco is a Max Weber post-doctoral Fellow at the European University Institute in Fiesole. She works on populism and electoral behaviour, negative campaigning and affective polarization. Her main interests concern the quantitative study of these phenomena, with an emphasis on cross- fertilization with computational sciences. She has recently published a paper in Political Analysis on the measurement of populism through the automated analysis of parties' national electoral manifestos. She is currently working with speeches, tweets and manifestos, as well as on more advanced computational approaches for populism measurement and the study of adjacent topics.
Link to Zoom meeting: https://univr.zoom.us/j/84004777179
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