Protests in Germany 2000–2020. A dataset based on local protest event data in Bremen, Dresden, Leipzig, and Stuttgart

In exploring protest dynamics, Protest Event Analysis (PEA) has proven an indispensable analytic tool. Despite various improvements, PEA faces continuous challenges, notably the reproduction of media-specific selection biases. This research note aims to contribute to the literature seeking to mitigate these issues by exploring the potential of PEA based on local newspaper data, which tend to be less selective in their protest reporting. The article introduces an original local PEA dataset in Germany (2000–2020) and systematically compares it to existing national-level PEA data for Germany. The analysis shows that while both datasets pick up similar trends in terms of mobilisation waves, national level data focus on shorter periods of intense protest activity. Furthermore, issues of protest differ: material and social issues (including labour and environmental issues) are more prominent in local data, while cultural issues (including immigration and gender) are more prominent in national-level data.

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.

Starting from a critique of protest event and political discourse analysis, we propose an extended methodological approach that has the quantitative rigor of event analysis but also retrieves the qualitative discursive elements of claims. Our political claims approach extends the sample of contentious actions beyond protest event analysis by coding institutional and civil society actors, and conventional and discursive action forms, in addition to protests by movement actors, This redefines the research object to acts of political claims making in a multi-organizational field. We use examples from a research project on mobilization about migration and ethnic relations in Britain and Germany to demonstrate the analytic gains that are possible with our approach. By situating protest and social movements, not just theoretically but also methodologically, in a wider context of political claims making, we are in a better position to follow the recent calls for more integrated approaches, which place protest within multi-organizational fields, link it to political opportunities and outcomes, and are sensitive to discursive messages.

In this study, we evaluated the differences between national and local newspapers coverage of the COVID-19 pandemic in Spain using a dataset of 421,438 Facebook posts. We assessed the trends in the interest in COVID-19 of local and national newspapers, measured as the proportion of COVID-19 news; and also, the trends in the interest of their readers, measured as the proportion of interactions related to COVID-19. While the overall interest in COVID-19 in local and national newspapers was similar and high, some differences were observed between several of the pandemic phases. National news media interest was higher during the long central phases of the pandemic, but certain news fatigue was observed by the end of 2021. Local news media interest seemed more constant throughout the pandemic. Surprisingly, the overall interest of national and local newspapers was consistently lower than the interest of their readers. Our study also shows homogenous responses among local newspapers during the key phases of the pandemic and heterogeneous responses in the remaining phases. Finally, we found that in the case of local media, their news and interactions were more correlated with the national epidemiological indicators (i.e., cases and deaths) than with the local indicators.

The pandemic did not bring protest politics to a halt. Instead, it sparked diverse and divergent forms of contention. This study compares the development and characteristics of anti-containment protests in Germany and Italy, offering three innovations. Conceptually, we introduce the notion of a protest script characterized by specific routinized dynamics and a contentious choreography, as well as frames expressed in slogans, banners, and speeches. Methodologically, we rely on video-enhanced protest event analysis (vPEA) to uncover these scripts, combining classical newspaper-based protest event data with video data analysis. Empirically, we show that the level of protest was higher in Germany than in Italy. Despite differences in the level and timing of protests, the study shows similarities and divergences in the countries’ protest scripts. Driven by far right and esoteric New Age actors, the protest events in both countries exhibit an escalating dynamic in terms of their choreography and the prevalence of conspiratorial and anti-systemic claims.

Protest event analysis is a key method to study social movements, allowing to systematically analyze protest events over time and space. However, the manual coding of protest events is time-consuming and resource intensive. Recently, advances in automated approaches offer opportunities to code multiple sources and create large data sets that span many countries and years. However, too often the procedures used are not discussed in details and, therefore, researchers have a limited capacity to assess the validity and reliability of the data. In addition, many researchers highlighted biases associated with the study of protest events that are reported in the news. In this study, we ask how social scientists can build on electronic news databases and computational tools to create reliable PEA data that cover a large number of countries over a long period of time. We provide a detailed description our semiautomated approach and we offer an extensive discussion of potential biases associated with the study of protest events identified in international news sources.

Internet Adoption and the Survival of Print Newspapers: A Country-Level Examination

Protest event analysis (PEA) and the related concept of repertoire of contention are widely used in the study of social movements. Are they appropriate for the study of feminist protest? I argue that conventional forms of protest event analysis may have significant limitations when applied to feminist protest. Unobtrusive or individualized forms of resistance and protest associated with feminism are difficult to measure through typical protest event data. Moreover, the concept of repertoires of contention retains within it a number of unwarranted gendered assumptions. Some flow from being too reliant upon protest event data. I suggest that repertoires may be gendered, that this is unacknowledged by those who use the concept, and that this has implications for its normative dimensions.

Using Computational Linguistics to Enhance Protest Event Analysis

The TV oak (Television Oak) conflict concerned felling an old tree in a wealthy area of Stockholm. The case received great public attention in different media formats with different scopes (e.g., newspapers, television, internet). The TV Oak issue involved actors with different, partly conflicting perceptions. Assuming that the relevance of urban tree management issues in particular leads to increased interest among the local audience, this paper compared differences in reporting on the TV Oak case in local and national newspapers. The comparison comprised the actors “speaking” in the newspapers, the interest roles attributed to different actors and the frames used. The empirical materials used were articles concerning the TV Oak published between October 2011 and June 2012 in one local and two national Swedish newspapers. Quantitative analysis of statements in these articles showed that the geographical scope of the newspaper was not the major driving force framing the TV Oak conflict and that variety of framings, ranging from a humanised perception of the oak to a more analytical hazard perception, were used. Differences between the interest roles allocated to different actors (e.g., in terms of victim, causer, and helper in the oak conflict) showed that the framing of conflicts very much depended on single actors, in particular a high profile journalist in the national newspapers and private individuals writing letters to the editor in the local newspaper.

This study investigated differences between how local and national newspapers framed race in their coverage of the 2007 Virginia Tech (VT) shootings. The results showed a local newspaper, with geographic and social ties to the VT community, published more stories about the shootings than did national newspapers and continued to publish articles well after the national newspapers had stopped. Further, national newspapers mentioned the shooter's race more often than did the local newspaper, despite having published fewer articles. The results also showed that national newspapers racialized the shooter more often and more prominently than did the local newspaper, but that the two newspaper types did not differ according to the levels of racialization each used (i.e., attributing the crime to the shooter himself rather than attributing it to his race), according to how racialized discussion of the shooting was, or in their use of implicit racialization.

Protest Event Analysis is important for government officials and social scientists. Here we present a new method for predicting protest events and identifying indicators of protests and violence by monitoring the content generated on Twitter. By identifying these indicators, protests and the possibility of violence can be predicted and controlled more accurately. Twitter user behaviors such as opinion share and event log share are used as indicators and this study presents a new method based on a Bayesian logistic regression algorithm for predicting protests and violence using Twitter user behaviors. According to the proposed method, users’ event log share behaviors which include the rate of tweets containing date and time information is the reliable indicator for identifying protests. Users’ opinion share behaviors which include hate-anger tweet rates is also best for identifying violence in protests. A dataset which consists of tweets that are generated on protests in the Black Lives Matter (BLM) movement after the death of George Floyd is used in the evaluation of the proposed method. According to information published on acleddata.com, protests and violence have been reported in various cities on specific dates. The dataset contains 1414 protest events and 3078 non-protest events from 460 cities in 37 U.S. states. Protest events in the BLM movement between May 28 and June 30 among which 285 were violent and 1129 were peaceful. Our proposed method is tested on this dataset and the occurrence of protests is predicted with 85% precision. It is also possible to predict violence in protests with 85% precision with our method on this dataset. This study provides a successful method to predict small and large-scale protests, different from the existing literature focusing on large-scale protests.

Chapter 1 Introduction: Protest as a Subject of Empirical Research Part 2 Methodological Issues Chapter 3 Studying Contentious Politics: From Event-ful History to Cycles of Collective Action Chapter 4 Methodological Issues in Collecting Protest Event Data: Units of Analysis, Sources and Sampling, Coding Problems Chapter 5 The Use of Protest Event Data in Comparative Research: Cross-National Comparability, Sampling Methods and Robustness Part 6 Protest and the Mass Media Chapter 7 Electronic and Print Media Representations of Washington, DC Demonstrations, 1982 and 1991: A Demography of Description Bias Chapter 8 Determining Selection Bias in Local and National Newspaper Reports on Protest Events Chapter 9 Unpacking Protest Events: A Description Bias Analysis of Media Records with Systematic Direct Observations of Collective Action-The 1995 March for Life on Washington, DC Part 10 Applications: Protest in Different Contexts Chapter 11 Plus ca change, moins ca change. Demonstrations in France During the Nineteen-Eighties Chapter 12 Radical Protest in Switzerland Chapter 13 Comparative Event Analysis: Black Civil Rights Protest in South Africa and the United States Chapter 14 Event Analysis in Transitional Societies: Protest Mobilization in the Former Soviet Union Chapter 15 Protest Event Analysis in the Study of Democratic Consolidation: Poland, 1989-1993

Protest event analysis (PEA) is the core method to understand spatial patterns and temporal dynamics of protest. We show how Large Language Models (LLM) can be used to automate the classification of protest events and of political event data more broadly with levels of accuracy comparable to humans, while reducing necessary annotation time by several orders of magnitude. We propose a modular pipeline for the automation of PEA (PAPEA) based on fine-tuned LLMs and provide publicly available models and tools which can be easily adapted and extended. PAPEA enables getting from newspaper articles to PEA datasets with high levels of precision without human intervention. A use case based on a large German news-corpus illustrates the potential of PAPEA.

The investigation of long-term trends in contentious politics relies heavily on protest event analysis based on newspaper reports. This tends to be problematic in restricted media environments. To mitigate the effects of bias and (self-)censorship, researchers of protest in authoritarian regimes have experimented with other sources such as international media and dissident websites. However, even though classical news media are easier targets for repression, journalistic reports might still outperform other sources regarding the quality of information provided. Although these advantages and disadvantages are known in the literature, different types of sources have seldom been tested against each other in an authoritarian context. Using the example of Russia between 2007 and 2012, the present article systematically compares protest event data from English-language news agencies, dissident websites, and several local sources, first and foremost with a view to improving methodological knowledge. The analysis addresses broad trends across time and space as well as the coverage of specific regions and single protest events. It finds that although the data sources paint different pictures of protest in Russia, this divergence is systematic and can be put to productive use. The article closes with a discussion on how its findings can be applied in other contexts.