Mobilizing or Demobilizing?: Measuring the Impact of Social Media in Elections

• In Event: Elections During the COVID-19 Pandemic

Abstract

Social media platforms and websites are assuming an ever more prominent role in elections as campaigners flood the internet with online ads, mobilizing hashtags and misinformation, and voters’ increasingly consume, share and comment on, this content. This prominence took on added relevance for elections held during 2020, given the shift of much of daily life to the online sphere in response to the Covid-19 pandemic. Given these developments building an accurate understanding of how this more immediate, immersive and interactive mode of communication is affecting voter behaviour and attitudes is both a pressing and very timely undertaking for researchers. To date, research on the topic to date has, by and large, supported the view that internet use and particularly social media has had a positive effect on individual’s political engagement, particularly within the electoral context (Boulianne, 2020). However, more recent studies have begun to suggest that a range of more negative behavioural, attitudinal and cognitive effects now need to be considered, with Facebook and other platforms seen as tools for demobilizing, dividing and disinforming electorates, fuelling distrust in mainstream politicians and the support for populist and extremist parties (Freelon and Lokot, 2020; Howard, 2020; Schroeder, 2019; Postill, 2018). More systematic investigation is currently needed to assess the extent to which the negative effects of social media and web use are now starting to outweigh their positive impact. In particular, models of internet use and political engagement need to be extended to specify and test for a range of explicitly anti-democratic outcomes, in addition to any democratic gains.
This paper seeks to address this challenge in by exploiting an innovative new research methodology that links individuals’ web activity with survey responses during the U.S. 2020 Presidential election. Specifically, we collected the Twitter use and web browsing habits of up to 1,500 respondents in a YouGov panel in the final two months of the campaign These data are combined with pre and post-election survey data measuring a range of political variables including vote intention, issue and ideological positions, levels of political interest, trust in the candidates and electoral system, and democratic satisfaction, as well as perceived exposure to misinformation during the election and knowledge about the current economic and health situation facing the U.S. Through the combination of these two types of data in a panel study design we are able to more accurately understand what voters saw, heard and did online during the election, and how this affected their likelihood of voting, sentiment toward the candidates, trust in key political actors and understanding of the key issues in the campaign. As such, we are able draw fresh and powerful insights into the causal impact of internet use on political engagement and particularly on this question of whether higher exposure to, and/or interaction with, online content is now leading to a net loss rather than net gain in electoral engagement? As well as looking at the impact of internet use on voter behaviour our dataset will also allow us to measure attitudinal and cognitive change among voters over the course of the campaign, and specifically whether increased reliance on digital media is linked with more negative perceptions and distrust of political elites, adoption or endorsement of more extremist views, as well as declines in political knowledge and the quality of voter decision-making. While our findings are not seen to provide a definitive answer as to whether the internet is now contributing to trends toward democratic backsliding, they are anticipated to offer fresh and important insight into this debate.

Authors

• Rachel K. Gibson, University of Manchester

• Jonathan Nagler, New York University

• Esmeralda V. Bon, University of Manchester

• Peter Smyth, University of Manchester

• Jahandar Musayev, The University of Manchester