Understanding Well-being Data

chapter 5 Getting a sense of Big Data and well-being

The darker side of historical well-being data and commercial gain

With the rise of market research came increased interest in people’s preferences, and in what made them happy or gave them pleasure [1]. This involved capturing subjective well-being data, as well as cultivating communications to imply that owning or consuming certain things would increase someone’s well-being in some way. The aim here in this context, of course, was to change people’s purchasing choices. With this shift, people as citizens became consumers. Over the years, ‘consumer sentiment’ indices have been assessed to see if these data can predict people’s behaviours on a macro level, from economic cycles [2] to presidential popularity [3]. This marriage of mood and economics is not new to us, of course. In Chap. 4, we encountered the development of subjective well-being data, a newer shinier well-being data, as a marriage of economics and psychology, known as happiness economics that was able to measure subjective well-being at population level.

Mood and sentiment analysis are not new, then. Neither are big datasets. Even Fitbits and Apple watches are not new; not really, as attaching technologies to people’s bodies has been used to study and improve productivity and surveillance of workers and citizens for around a hundred years [4]. So, what is new? The amount and variety of data on the well-being of individuals and populations are increasing as technologies develop to manage greater amounts of different kinds of data, not only faster, but faster together.[5] Therefore, it is not necessarily how one thing (not that Big Data are one thing, really) is new. Instead, it is a far more complex picture of how different aspects of, and different people across fields of, politics, science, research and technology work together—and work with commerce. These all combine as developments in what we know, and ways of knowing, about society.

The question is, what does that mean for well-being? How can we learn from previous mistakes regarding the context of who is using what data— and to what end? COVID-19 will offer us many data insights and many insights into how data can help us understand and look after well-being better. The next section looks at the role of data and learning in a pandemic, of old and new infrastructures and commercial and governmental data practices in the management of a pandemic.


  1. Davies 2015; Savage 2010[]
  2. Carroll et al. 1994[]
  3. Suzuki 1992[]
  4. Davies 2015; Cryle and Stephens 2017[]
  5. Several new methodologies are emerging that propose new possibilities for well-being measurement through combining new data sources with the survey data we have explored in previous chapters (Bellet and Frijters 2019; Daas et al. 2013; Jahani et al. 2017). These are not only hoping to understand well-being as personal or subjective experience, but to change the way that social justice issues such as poverty are approached (Blumenstock 2016). International organisations such as the United Nations are supporting this kind of work, although primarily focussing on patterns of ‘health and well-being’ (United Nations 2014, 2015).[]