Project description
Playing the blame game on Twitter
To appease citizens when unpopular policies are applied, some governments resort to a communication strategy named blame avoidance. However, little is known about the uses and implications of this strategy in social media. The EU-funded BAIT project will provide new knowledge about this type of communication. It will study Twitter since it is an influential social media channel in wide use amongst politicians, activists and voters. The project focuses on Brexit considering it a key example of how governments may react to serious blame risk. BAIT will identify the discursive features of blame avoidance used in Twitter, investigate how different forms of blame avoidance may affect people, and communicate the research findings to a wide-ranging audience.
Objective
Blame avoidance is a key communication strategy used by government officials when they initiate unpopular policies, but has not yet been studied for its use in social media. ‘Blame Avoidance in Twitter’ (BAIT) is a project which generates new knowledge about this important form of communication by analysing data from Twitter as an influential site used by politicians, activists and citizens. We take the recent, controversial decision of the British government to leave the European Union, as a timely and high-scale case study which offers lessons to other European countries about how governments may respond to acute blame risk. The objectives of BAIT are: (1) to establish and quantify the discursive features of blame avoidance used in Twitter debates; (2) to evaluate the effects of blame avoidance expressed in Twitter, through analysing the responses that arise in the form of replies and retweets; (3) to investigate how blame avoidance affects how people think and feel; (4) to disseminate the findings of the project to academics and the wider public, including politicians and activists. We will achieve this with an interdisciplinary approach which bridges the macro-social interests of political science and micro-analytic foci of linguistics, using mixed methods in a series of three studies. The first study uses corpus linguistics to quantify the forms of blame avoidance in a specialised corpus created from Twitter hashtag threads related to Brexit. The second study analyses replies to tweets containing blame avoidance, using critical discourse analysis to analyse the extent to which such posts gain support or criticism. The third study uses in an online survey experimental task to examine how the language used in blame avoidance affects citizens’ perceptions of politicians. The results of BAIT will be published in articles, an edited collection and a series of public engagement activities.
Fields of science
Not validated
Not validated
Programme(s)
Funding Scheme
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinator
B15 2TT Birmingham
United Kingdom