Sage Journals - July 2017
A growing social science literature has used Twitter and Facebook to study political and social phenomena including for election forecasting and tracking political conversations. This research note uses a nationally representative probability sample of the British population to examine how Twitter and Facebook users differ from the general population in terms of demographics, political attitudes and political behaviour. We find that Twitter and Facebook users differ substantially from the general population on many politically relevant dimensions including vote choice, turnout, age, gender, and education. On average social media users are younger and better educated than non-users, and they are more liberal and pay more attention to politics. Despite paying more attention to politics, social media users are less likely to vote than non-users, but they are more likely to support the left leaning Labour Party when they do vote. However, we show that these apparent differences mostly arise due to the demographic composition of social media users. After controlling for age, gender, and education, no statistically significant differences arise between social media users and non-users on political attention, values or political behaviour.
Political research using social media data has expanded rapidly, with studies using data from Facebook and Twitter to forecast elections (Tumasjan et al., 2010; Sang and Bos, 2012; McKelvey et al., 2014; Burnap et al., 2015), and study online deliberation (Larsson and Moe, 2011), political mobilization (Carlisle and Patton, 2013; Vissers and Stolle, 2014), and political ideology (Barbera, 2014; Bond and Messing, 2015). More generally, political actors and the media often pay attention to issues brought up on social media. For both academic and democratic reasons it is important to know how wide a slice of society these platforms represent.
Many of these studies focus only on the platform itself, but several (particularly those using social media to forecast elections) focus on wider trends in public opinion and political behaviour. As with other types of non-probability samples (e.g. for the challenges facing non-probability Internet panel surveys, see Baker et al., 2013) inferences from social media data run the risk of error if there are non-ignorable confounding relationships between the probability of self-selection into samples and outcome variables of interest.1
Survey analysis of social media demographics in the US have shown that Facebook and Twitter users tend to be younger and more educated than the general population, with Twitter having a more skewed distribution (Duggan, 2015; Greenwood et al., 2016). Studies using geotagged US Twitter data have found that Twitter users are more commonly found in urban areas (Mislove et al., 2011) and particularly wealthier areas with younger populations (Malik et al., 2015). Looking more specifically at the political attitudes of Twitter users, a study of the 2011 Spanish elections and the 2012 US presidential election showed that politically active Twitter users skew male, urban and politically extreme (Barbera and Rivero, 2014). Similarly, a survey of politically active Italian Twitter users showed that they were younger, better educated, male and left wing (Vaccari et al., 2013).
It is clear from previous research that social media users are not demographically representative of the population. However the question remains whether, when controlling for demographic variables, there remain unobserved, non-ignorable, differences between social media users and non-users. If there are non-demographic differences in the data, adjusting it with weights to appear demographically representative could lead to large errors (Mellon and Prosser, 2017) and would require more sophisticated adjustment methods (e.g. Wang et al., 2014). ...
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