Since the early 2000s, the proliferation of cameras, whether in mobile phones or CCTV, led to a sharp increase in visual recordings of human behavior. This vast pool of data enables new approaches to analyzing situational dynamics. Application is both qualitative and quantitative and ranges widely in fields such as sociology, psychology, criminology, and education. Despite the potential and numerous applications of this approach, a consolidated methodological frame does not exist. This article draws on various fields of study to outline such a frame, what we call video data analysis (VDA). We discuss VDA’s research agenda, methodological forebears, and applications, introduce an analytic tool kit, and discuss criteria for validity. We aim to establish VDA as a methodological frame and an interdisciplinary analytic approach, thereby enhancing efficiency and comparability of studies, and communication among disciplines that employ VDA. This article can serve as a point of reference for current and future practitioners, reviewers, and interested readers.

No abstract

Since the turn of the millennium researchers have access to an ever-increasing pool of novel types of video recordings. People use camcorders, mobile phone cameras, and even drones to film and photograph social life, and many public spaces are under video surveillance. More and more sociologists, psychologists, education researchers, and criminologists rely on such visuals to observe and analyze social life as it happens. Based on qualitative or quantitative techniques, scholars trace situations or events step-by-step to explain a social process or outcome. Recently, a methodological framework has been formulated under the label Video Data Analysis (VDA) to provide a reference point for scholars across disciplines. Our paper aims to further contribute to this effort by detailing important issues and potential challenges along the VDA research process. The paper briefly introduces VDA and the value of 21st century visuals for understanding social phenomena. It then reflects on important issues and potential challenges in five steps of conducting VDA, and formulate guidelines on how to conduct a VDA: From setting up the research, to choosing data sources, assessing their validity, to analyzing the data and presenting the findings. These reflections aim to further methodological foundations for studying situational dynamics with 21st century video data.

Objectives: This article investigates how situational dynamics influence the emergence of protest violence. Although common-sense explanations of violence focus on actors’ motivations and strategies, a situational turn is underway, emphasizing the relevance of the violent situation itself. This article assesses this situational approach, examining whether the emergence of violence can be explained by focusing on what occurs during a protest. Method: The article comparatively analyzes 30 protests occurring in the United States and Germany between 1960 and 2010. Using a triangulation of visual and document data, as well as participant observation, it analyzes over 1,000 data pieces, uses 2 samples, and conducts 3 steps of analysis: The article develops a situational approach using meticulous case reconstructions (employing Video Data Analysis), tests the approach by comparatively analyzing a random sample of violent and peaceful protests (employing Qualitative Comparative Analysis), and revisits cases to identify crucial dynamics and paths to protest violence. Results: The study identifies 5 behaviors by protesters and police during protests crucial for leading to violence if they occur in one of the following three combinations: a loss of control path, a missing information path, and an offense path. All 3 combinations trigger violence by changing actors’ situational interpretations and emotional dynamics. Conclusions: Findings suggest a purely situational approach—focusing on what happens during demonstrations—can provide a consistent and meaningful explanation for the emergence of violence. Alternative explanations are discussed, such as the relevance of background and context factors as risk factors to the emergence of violence.

Objective: This article analyzes how convenience store robberies work and why some take an unexpected turn and fail. It examines the situational dynamics of crime by studying behavioral and emotional dynamics between clerks and perpetrators during robberies comparatively. The focus is on perpetrators’ displays of threats and clerks’ seemingly irrational acts of noncompliance and resistance. Method: The sample is comprised of 20 successful and failed robberies in the United States between 2010 and 2016. By qualitatively analyzing closed-circuit television (CCTV) recordings, the study assesses what happens during such crimes. Analyzing footage uploaded to online video platforms such as YouTube, the study uses growing databases so far unexplored by sociological and criminological research. Findings suggest that successful store robberies follow specific situational rituals in which actors display adequate behaviors and emotions. Rituals are broken if perpetrators or victims act out of character and display, even unintentionally, unexpected behaviors or emotions. Conclusion: This exploratory study suggests that microlevel factors play a crucial role in what manifests as a robbery versus attempted robbery. Further, it highlights challenges and advantages of analyzing CCTV recordings uploaded online when studying crime caught on camera.