Understanding Well-being Data

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

Social media data – a game changer?

I am sure that social media plays a role in unhappiness, but it has as many benefits as it does negatives.

(Sir Simon Wessely, president of the UK’s Royal College of Psychiatrists in Campbell 2017)

Social media platforms have an interesting relationship to well-being. They are often demonised as bad for well-being, especially for the younger generation who are thought to dwell on images of idealised bodies and lifestyles on Instagram1. All ages feel a pang looking at the picture-perfect presentations on Facebook, and even the NHS warns people to take breaks from social media2. Credible, successful women leave themselves vulnerable to criticism from strangers in the sharing of thoughts, opinions and aspects of their identity on platforms like Twitter3. Similarly, hate speech against people of colour4 or for their gender identity5 are realities of social media platforms. However, social media and online platforms also offer places for human connections, and have had beneficial effects for the social isolation brought about by measures to curb the spread of COVID-19. The jury is still out on many of the pros and cons of social media, including their propensity to spread disinformation, versus credible analysis of data and guidelines. Social media therefore hold an ambivalent place in the management of well-being.

These controversial aspects of social media are not their only connections to well-being. The data we share can make them useful for well-being analysis. The most mundane aspects of our feeds, the venting of minor irritations, celebrations of small wins or just feelings shared with friends and family mean our social media accounts are full of well-being data. Think about those ONS4 questions again (Table 4.2) that aim to gauge ‘personal well-being’. For example, they all ask you to think about how you felt yesterday overall—in terms of happiness or anxiety, as well as whether you think what you do is worthwhile, and whether you are satisfied with your life. When you think about Facebook’s most prolific posters in your timelines, for example, much of their content will indicate how they felt in similar ways at specific moments. The recent addition of emojis to Facebook means it is easier to proclaim whether you were happy, celebrating or anxious. The reminders of what you were doing this time last year or ten years ago means we are telling everyone on Facebook how we feel now, about how we were feeling in previous years. Crucially, this means it is even easier for Facebook to know this too, as you have essentially coded your own data for them.

This compulsion to share how we feel means we are also sharing our data with Facebook and other platforms. These platforms are able to analyse us alongside millions of others at scale. Companies like Brandwatch monitor social media and analyse several billion emoticons each year to inform brands whether they are provoking hatred or happiness with their products. It is also possible for a broad range of actors to mine social media data, whether commercial companies, government agencies, academic researchers or amateurs with the inclination to do so. The platforms are set up with open Application Programming Interfaces (APIs). APIs are what allow other (data mining) software to interact with social media platforms. Once access to social media data has been gained, it can be ‘scraped’ with comparative speed with the right skills and software. Scraping is a process which essentially involves gathering and copying data that meets specific search terms. It is then put into a database (that can be as crude as a spreadsheet), for later retrieval or analysis. This can be done by a person, although the term more typically refers to automated processes involving a bot or web crawler. The fact that APIs are generally open as a standard indicates that these data—your data—are made available by social media platforms to be used by various different actors. Not many people think about the fact that their public post on a social media platform is public in the sense that it is no longer their private property and can be used by others in research.((For the ethical concerns regarding social media research, see Townsend and Wallace (2016).))

There are practical limits to what can be known through analysing people’s social media posts, of course. First, people are not neutrally representing themselves on social media. As we know, people feel compelled to publish reflections on an idealised version of their lives6. Of course, our social media posts don’t always represent our lives as happier than they actually are: people often exaggerate the impact of minor negative events that are as mundane as missing the bus or being rained on. Some people collectively engage in dissatisfaction with their lot in life, leading to Twitter bubbles and what has become known as ‘the culture wars’,(( See Davies 2018 for a discussion on the greater implications of ‘the culture wars’ for politics and community)) as the contemporary cultural conflict between social groups. This term describes a gap between those who side with a traditional, conservative approach, and those with a liberal, progressive approach to society and social issues, such as immigration, abortion, LGBTQIA+ rights, and so on. The contemporary culture wars, as a struggle for dominance of values and beliefs, now takes place on Twitter, and we might question the extent to which such rage and passion are indicative of someone’s personal well-being, or some form of tribal rage on a larger scale. Essentially, we are seeing how important social media can be in both distorting and shaping our well-being for better or for worse. The key to appreciating the relationship of social media, data and well-being is understanding limits and context—of collection and use.

  1. Campbell 2017 []
  2. NHS 2016 []
  3. Lewis et al. 2016 []
  4. Gayle 2018 []
  5. Pearce et al. 2020 []
  6. Kruzan and Won 2019 []