Social media data in affective science

Abstract

The digital traces generated by social media offer the opportunity to analyze human behavior at new scales, depths, and resolutions. The results of analyses of social media data, while sometimes difficult to generalize to a society as a whole, can give important insights on detailed actions and subjective states of individuals. This novel datasource offers a new window to tackle research questions from affective science with respect to emotion dynamics, collective emotions, and affective expression in social contexts. In this chapter, we present a balanced view of the benefits, risks, opportunities, and pitfalls of analyzing affective life through social media data. We review a variety of methods to quantify emotions and other affective states from social media data. We illustrate the application of these methods at new scales and resolutions in a series of examples from previous research. We present research gaps and open questions about the role, meaning, and functionality of affective expression in social media, pointing to emerging research trends in computational social science and social psychology. When used critically and with robust research methods, observational analyses of large-scale social media data can be complementary to traditional methodologies in psychology and cognitive science.