Video Data Analysis (VDA) is a curated multi-disciplinary collection of tools, techniques, and quality criteria intended for analyzing the content of visuals to study driving dynamics of social behavior and events in real-life settings. It often uses visual data in combination with other data types. VDA is employed across the social sciences such as sociology, psychology, criminology, business research, and education research.
General approach VDA makes use of technological and social developments in relation to video recordings. Mobile phone cameras, CCTV surveillance cameras, body-worn cameras, and other types of cameras generate an ever-expanding pool of recordings from real-life situations. More and more of these videos are uploaded to internet platforms such as Snapchat, TikTok, Instagram, LiveLeak, YouTube, Facebook, and many others. Others can be accessed through collaboration with public and private institutions, such as police departments or CCTV providers. Parallel to this increase in third-hand video data, advances in camera and data storage technology also enabled new ways of collecting first-hand videos for research, by researchers. In short, humans find themselves in a new era of how social life is captured. These new sources of video data support researchers in unobtrusively collecting video recordings that depict real-life situations even of extremely rare events that would be otherwise impossible for researchers to observe first hand. VDA relies on these types of videos to analyze real-life social processes and events—tracing them step-by-step to explain how they unfold. To do so, VDA draws on methodological approaches such as visual studies, ethnography, video-based experimental psychology, and multimodal interaction analysis to provide a multi-disciplinary approach to using video data. Foci of such analyses include sequences of peoples' interactions, movements, fields of vision, exchanges of glances or gestures, and actors' facial expressions and body postures. The goals of VDA studies are to further our understanding of the rules, processes, and sequential patterns that govern social life on the micro level, both in everyday encounters and extreme situations. The method can also be used to trace influence of structural factors in social interactions and events, or study how patterns in social interactions and events produce macro-level phenomena. At the core of this perspective lies the question: How do social actions and situational dynamics impact social outcomes? Video data offers the possibility to study situational patterns in unprecedented detail and rigor by allowing researchers to replay situations, watch them in slow motion and fast forward, and share primary data of situations with colleagues and readers. VDA outlines a toolkit of analytic dimensions and procedures, introduces criteria of validity, and discusses challenges and limitations.
Areas of application VDA is employed in disciplines such as sociology, psychology, criminology, business research, and education research to study a variety of phenomena, including armed store robberies or unattended package theft, the situational dynamics of protests and uprisings, or physical violence, such as street fights and massacres. Others have used the approach to study polarization among politicians, YouTuber staged health practices, teacher competence, school yard fights, or consoling behaviors. VDA has also been applied to study military negotiations, the unfolding of emergency evacuations, as well as police use of force and police training
… excerpt ends here. Continue reading the full article.
