Moral Expressions in 280 Characters or Less: An Analysis of Politician Tweets Following the 2016 Brexit Referendum Vote

Abstract

Ideas about morality are deeply entrenched into political opinions. This article examines the online communication of British parliamentarians from May 2017-December 2019, following the 2016 referendum that resulted in Britain's exit (Brexit) from the European Union. It aims to uncover how British parliamentarians use moral foundations to discuss the Brexit withdrawal agreement on Twitter, using Moral Foundations Theory as a classification basis for their tweets. It is found that the majority of Brexit related tweets contain elements of moral reasoning, especially relating to the foundations of Authority and Loyalty. There are common underlying foundations between parties, but parties express opposing viewpoints within a single foundation. The study provides useful insights into Twitter’s use as an arena for moral argumentation, as well as uncovers the politician’s uses of moral arguments during Brexit agreement negotiations on Twitter. It contributes to the limited body of work focusing on the moral arguments made by politicians through Twitter.

Moral expressions, sources, and frames: Examining COVID-19 vaccination posts by facebook public pages

“…The amount of moral expression in our data is relatively high, compared to previous studies on other social media content such as Twitter discussions ( Matsuo et al, 2021 ; Mutlu et al, 2020 ; Van Vliet, 2021 ). This suggests that talking about COVID-19 vaccine in a moral way is a common practice on Facebook public pages.…”

A Systematic Evaluation of Text Mining Methods for Short Texts: Mapping Individuals’ Internal States from Online Posts

“…Studying emotions, attitudes, and moral norms individuals expressed in everyday texts can support our understanding of, for instance: the dynamics of public opinion and affective polarization (DiMaggio, Evans, and Bryson 1996;Evans, Bryson, and DiMaggio 2001;Garrett and Bankert 2020;Rapp 2016); the ways in which individuals respond to political pressure or affective and moral persuasive messages in the public sphere (Boltanski and Thévenot 2000;Downey 2022;Friedkin 1999;Goode and Ben-Yehuda 1994); the unravelling of social influence when it comes to opinion change (Friedkin and Johnsen 1990); or the emergence of personal culture (Elliot et al 2014;Hitlin and Vaisey 2013;Kiley and Vaisey 2020;Longest et al 2013). Recent work in sociology and other fields has showcased how text mining can be used to trace the effect of social motives in text on the opinion change (Monti et al 2022), pervasive power of morally loaded texts (Spörlein and Schlueter 2021;van Vliet 2021), or even evaluate subjective well-being or opinion distributions at a population level (Amador Diaz Lopez et al 2017;Garcia et al 2021;Jaidka et al 2020;Mozes et al 2021;Skoric, Liu, and Jaidka 2020).…”

“…Research in political science, psychology, and computer science has given us indications that internal states can be explored in textual data (Amador Diaz Lopez et al 2017;Dehghani et al 2014;Hasan and Ng 2014;Kröll and Strohmaier 2009;Liu et al 2012;Mooseder et al 2022;Prabhakaran, Rambow, and Diab 2012;Schultheiss 2013;van Vliet 2021). 1 Psychological research has extensively validated inference on personality traits in text (Bleidorn and Hopwood 2019;Eichstaedt et al 2021;Pennebaker, Mehl, and Niederhoffer 2003;Tay et al 2020), while recent research in other fields shows that measures of other internal states extracted from texts compare well to those obtained using other methods at both individual (Eichstaedt et al 2021;Kennedy et al 2021;van Loon and Freese 2022;Lykousas et al 2019;Malko et al 2021;Matsuo et al 2019;Mozes, van der Vegt, and Kleinberg 2021;Pellert et al 2022) and aggregate (Amador Diaz Lopez et al 2017;Garcia et al 2021;Jaidka et al 2020) levels of measurement.…”