Using Big Data to study subjective well-being

•Reviews how Big Data are used to measure, study, and change subjective well-being (SWB).•The most popular measurement approach is the analysis of language patterns on Twitter or Facebook.•Other approaches include the analysis of Facebook profiles and mobile phone usage patterns.•Big Data measures appear reliable and valid for emotional well-being, but not yet for life satisfaction.•Big Data may be particularly valuable for tracking SWB across time and space.

Subjective well-being comprises emotional experiences and life satisfaction. This article reviews how Big Data can be used to measure, study, and change subjective well-being. Most Big Data approaches measure subjective well-being by analyzing language patterns on Twitter or Facebook. These approaches provide satisfactory accuracy for emotional experiences, but not yet for life satisfaction. Other measurement approaches include the analysis of other digital traces such as Facebook profiles and the analysis of mobile phone usage patterns. Big Data can be used to study subjective well-being on individual levels, regional levels, and across time. Potentials and limitations of using Big Data in studies on subjective well-being are discussed.