Browsing by Author "Mackay, Claire Louise"

The language of evaluation enables us to share opinions, cement values, and create interpersonal meaning. It is a fundamental aspect of both social media communication and political discourse. This study uses Martin and White’s (2005) Appraisal Framework to investigate how political actors use evaluation to express emotions and confer judgement in their attempts to increase support on social media. Drawing on a corpus of 1,212 tweets from Boris Johnson and Jeremy Corbyn during the 2019 British General Election campaign, this study focuses on how the individual politicians use ATTITUDE to build positive-self and negative-other evaluations. The analysis then considers the wider performance of populism in political discourse by examining positive appraisals of the people, presented against negative judgements of a corrupt elite. Finally, the thesis explores how specific Twitter features can be incorporated into the Appraisal Framework to better capture evaluation in tweets as complete objects. Contrary to expectations about the prevalence of negative messaging in electoral campaigns, the findings show that both candidates preferred to post positive evaluations on Twitter. Corbyn favoured judgements of his party that empathised their moral superiority (PROPRIETY), and Johnson praised his party for their ability to negotiate a departure from the EU (CAPACITY). Both candidates performed elements of populism, but the presentation and evaluation of the people was very different, with Johnson performing an exclusionary form of populism and Corbyn presenting a more inclusionary form. Whilst there are challenges in applying the Appraisal Framework to online campaigning, the results give a much more nuanced understanding of the evaluation inherent to this discourse than automated sentiment analysis is able to, particularly in identifying the interplay of positive-self and negative-other evaluation. However, Appraisal reaches beyond the text, and many features were present in the media attached to the tweets, and future studies would benefit from incorporating these aspects into the analysis. The evaluative force of other resources, such as emoji and hashtags, and Twitter practices, such as retweeting, should similarly not be underestimated, and this study concludes by suggesting how these aspects can be brought into the Appraisal Framework.