Summary
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.
Unfold all
/
Fold all
More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/891933 |
| Start date: | 12-10-2020 |
| End date: | 11-10-2022 |
| Total budget - Public funding: | 212 933,76 Euro - 212 933,00 Euro |
Cordis data
Original description
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.Status
CLOSEDCall topic
MSCA-IF-2019Update Date
28-04-2024
Geographical location(s)
