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Expanding protest event analysis through videos

[journal article]

Della Porta, Donatella
Hunger, Sophia
Hutter, Swen
Lavizzari, Anna

Abstract

The increasing availability of digital video material has led to its widespread use in the social sciences, especially in research adopting processual and relational approaches. However, methodological reflection has not developed at the same pace. In this article, we propose ways to extend classica... view more

The increasing availability of digital video material has led to its widespread use in the social sciences, especially in research adopting processual and relational approaches. However, methodological reflection has not developed at the same pace. In this article, we propose ways to extend classical protest event analysis using videos of contentious events. Our novel method, video-enhanced protest event analysis (vPEA), expands protest event research on two frontiers. First, researchers can use vPEA extractively, contributing to source triangulation and increasing the validity of written sources. Second, it can be used reconstructively, expanding the range of information available by capturing emotional atmosphere, choreography, and processes and dynamics more generally. The article provides a step-by-step guide through the vPEA process, which we illustrate using a secondary analysis of existing research and original material on Covid-related protests in Germany and Italy.... view less

Keywords
protest; data capture; video

Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods

Free Keywords
digital data; protest event analysis; triangulation; video analysis

Document language
English

Publication Year
2024

Page/Pages
p. 245-262

Journal
Mobilization: An International Quarterly, 29 (2024) 2

DOI
https://doi.org/10.17813/1086-671X-29-2-245

ISSN
1938-1514

Status
Postprint; peer reviewed

Licence
Deposit Licence - No Redistribution, No Modifications


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© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.