The US passed 2.5 million Covid-19 cases, there are more than 10 million confirmed cases worldwide, and global deaths passed 500,000 at the end of June. We face unprecedented challenges during this global pandemic and we may see profound and permanent changes to how we do things. Surveys and digital trace data have been used extensively to study these changes, but another unique source of insight has been used much less: videos. In the following, we will focus on two ways in which social science research can study human interaction during the Covid-19 pandemic. How do people adapt to social distancing and mask-wearing? How do interactions unfold during video calls?
First, analyzing CCTV data from before and during the pandemic may allow observing changes in public behavior during the pandemic and conduct comparisons of pandemic-related interaction in different neighborhoods, regions, or countries. Surveys aimed to analyze who goes outside, how often, and how long, or who wears a mask, might suffer from social desirability; i.e., people may overstate their compliance with public norms. Videos can show us how people actually behave in public spaces during the pandemic: Who wears a mask and who does not? Are there visible differences in gender expression or age, or in different countries? Do individuals adapt their behavior if they encounter others who wear a mask, or who socially distance more or less than they do? How do people negotiate public space as the pandemic unfolds, and when do more people start to adhere to distancing and mask-wearing guidelines? Are there new ways in which people display solidarity with each other in public spaces? Today, researchers do not need to produce video data themselves, at potentially high costs and with potentially limited coverage of different sites. Instead, recordings can be collected through CCTV providers and social media sites. Some websites, such as earthcam.com, even stream CCTV camera footage from across the globe, 24 hours a day. In real-time we can watch social life during the pandemic in Tokyo, Toronto, or Times Square. We can observe social distancing on beaches in the US, Thailand, or the Maldives. These data also allow us to observe reactions to the pandemic across time. CCTV and smartphone cameras are essentially “always on,” meaning they continuously produce videos for non-academic purposes or as a byproduct of online interactions –similar to digital traces such as Google searches, as described by Matthew Salganik in his book “Bit by Bit.” This means we can go back in time and look at real-life interactions captured on CCTV before the pandemic to compare them to human interaction during and after. We can even use additional sources, such as national and local infection or death rates, to infuse the analysis with context information and analyze if and how they impact behavior on the ground.
Second, use of video conference services increased exponentially during the Covid-19 pandemic. Every day people film millions of family meetings, Friday night drinks, and business meetings. Some recordings show breakups, others marriage proposals, online teaching and students’ reactions, or toddlers playing. Direct access to such data is, of course, impossible and unwarranted; from a research ethics standpoint, we cannot just log into a video call and record people. And even collaborating with providers to analyze recordings the company keeps would be concerning from a research ethics standpoint. People may not even be aware that their, potentially very private, exchanges are stored by a company, much less did they consent to the recordings being analyzed by social scientists. But there may be a way to tap into this wealth of data on social interactions while respecting people’s privacy and the need for consent. Scholars are increasingly using mass collaboration to collect and process digital data, as shown by initiatives such as eBird, PhotoCity, Galaxy Zoo, or FoldIt. Researchers have also used collaboration to collect video data of interactions, e.g., in families, such as the New Jersey Family Study, as well as videos to train human action recognition software, such as the Charades dataset. Similar mass collaboration could allow collecting extensive video data of virtual face-to-face interactions, if people respond to a call for collaboration. This approach would entail a number of requirements: all participants in a given call would need to consent to being filmed and the video being used for research, and scholars would need to ensure the safe storing of such data and the protection of privacy. Studying these videos may provide crucial insight into social life: from speech patterns and mimicking behaviors in successful versus unsuccessful business negotiations, to gender-bias in speech interruptions during virtual workplace meetings, or emotional contagion in virtual friends’ hangouts. A large field of scholars across the social sciences assume that these types of interactions constitute the fabric of social life. They make up what we end up calling a “workplace,” “family,” “gender inequality,” or “friendship.” Beyond mundane interactions, the platforms we use so extensively at the moment also record extraordinary (and sometimes horrific) events usually not caught on video. In late May, the video-chat platform Zoom recorded a man fatally stabbing his father while the latter was in a zoom meeting with 20 other participants. The video includes not only the stabbing, but also participants’ reactions to the events, such as calling the police.
With video recordings capturing more and more aspects and moments of our social lifes, the Covid-19 pandemic further exacerbates this development. Social research has tools at hand to use such data and help us observe and understand while social life is reorganizing around us. As sociologist Randall Collins puts it: “Everything observable is an opportunity for sociological discovery.”