Abstract
Modern politics is permeated by blame games-symbolic struggles over the blameworthiness or otherwise of various social actors. In this article, we develop a framework for identifying different strategies of blaming that protesters use on social media to criticize and delegitimize governments and political leaders. We draw on the systemic functional linguistic theory of Appraisal to distinguish between blame attributions based on negative judgments of the target's (1) capacity, such as references to their incompetence and policy failures; (2) veracity, questioning their truthfulness or honesty via references to deceitful character or dishonest acts and utterances; (3) propriety, questioning their moral standing by references to, for instance, corruption; and (4) tenacity, suggesting that the politicians are not dependable due to, for example, dithering. We add to this a further threefold distinction based on whether blaming is focused on the target's (1) bad character, (2) bad behavior, or (3) negative outcomes that the target either caused or did not prevent from happening. To illustrate the approach, we analyze a corpus of replies by Twitter users to tweets by British government ministers about two highly contentious issues, Covid-19 and Brexit, in 2020-2021. We suggest that the methodology outlined here could provide a useful avenue for systematically revealing and comparing a variety of realizations of blaming in large datasets of online conflict talk, thereby providing a more fine-grained understanding of the practices of protest and delegitimation in modern politics.