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.

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Google search data have several major advantages over traditional survey data. First, the high costs of running frequent surveys mean that most survey questions are only asked occasionally making comparisons over time difficult. By contrast, Google Trends provides information on search trends measured weekly. Second, there are many countries where surveys are only conducted sporadically, whereas Google search data are available anywhere in the world where sufficient numbers of people use its search engine. The Google Trends website allows researchers to download data for almost all countries at no cost and to download time series of any search term's popularity over time (provided enough people have searched for it). For these reasons, Google Trends is an attractive data source for social scientists.

In this chapter we show how the twin processes of partisan dealignment and party system fragmentation have underpinned the increase in electoral volatility. Fragmentation creates volatility because smaller parties consistently lose a much higher proportion of their voters between elections than the major parties. Partisan dealignment matters because there is a strong and consistent relationship between a voter’s level of partisanship and the likelihood of them switching parties at the next election. While this accounts for a substantial proportion of the trend in volatility, it is less clear why partisan identification has itself declined. We show a clear pattern of generational replacement in partisan identification, with newer cohorts entering with lower levels of partisanship and remaining relatively stable over time.