![]() Acknowledging and working with these issues is key to ethical computational social science that promotes real societal progress. These digital traces tend to be left disproportionately by relatively wealthy people in developed countries, biasing attempts to draw global conclusions. There are also concerns that people whose data are being used have not fully consented to this - and wider worries about the economic monopoly of tech corporations that own the majority of the data. These include risks from increased surveillance, and the danger that people could be reidentified from otherwise anonymized data.Įveryone should decide how their digital data are used - not just tech companies Power and responsibilityĪt the same time, researchers need to remember that gathering and sharing such personal data - practices that are currently largely unregulated - pose many challenges to society. And its availability puts it in reach of practically every social-science discipline: researchers in fields from psychology to economics and political science can now rely on data to enhance investigations of key societal questions. But the wealth of real-time and individual-level information is now unparalleled in its power to track trends, make predictions and inform decisions. Using computers to analyse large data sets dates back to the earliest mainframe computers - and has been central to the work of actuaries and national statistics offices, both of which have long been important resources for studies of society and people. They have been able to access anonymized credit-card purchase histories to study how people are spending money during the pandemic - information which is then used to understand how COVID-19 is affecting various sectors of the economy. Nature special: Computational social scienceĭuring the course of the coronavirus pandemic alone, researchers have been able to access millions of mobile-phone records to study how people’s movement changed during the pandemic and the impact of those changes on how SARS-CoV-2 spread. ![]() As a result, work weaving large data analysis with social questions, known as computational social science, has witnessed huge growth in recent years. These include data that trace people’s movements, purchases and online social interactions - which are all proving extraordinarily powerful for research. Moreover, it is difficult to obtain large amounts of data simultaneously.īut now, researchers have access to an unprecedented amount of social data, generated every second by continuous interactions on digital devices or platforms. ![]() Carrying out research in this way is a time-consuming and manual process. Social scientists researching these questions observe how people behave, record data on those behaviours and then augment this knowledge by interviewing and/or polling those whom they are studying. What are the causes of vaccine hesitancy? How can people be encouraged to exercise more? What can governments do to improve the well-being of citizens? Credit: Paul Seheult/Eye Ubiquitous/Universal Images Group/Getty Computational social scientists have been using data from mobile phones to study the coronavirus pandemic.
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