Dialogic analysis of government social media communication: How commanding and thanking elicit blame

IF 2.3 2区 文学 Q1 COMMUNICATION Discourse Context & Media Pub Date : 2024-02-01 DOI:10.1016/j.dcm.2024.100757
Ruth Page , Sten Hansson
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引用次数: 0

Abstract

During major crises, such as the Covid-19 pandemic, government officeholders issue commands to change people’s behaviour (e.g., ‘Stay at home!’) and express thanks to acknowledge the efforts of others and build solidarity. We use specialised datasets of replies to social media posts by government ministers in the United Kingdom during Covid-19 lockdowns to explore how people react to their messages that contain directive speech acts and thanking. Empirically, our corpus-assisted analysis of evaluative language and blaming shows that far from promoting team spirit, thanking may elicit at least as much, if not more blaming language than commands. Methodologically, we demonstrate how to analyse government social media communication dialogically to gain more nuanced insights about online feedback from citizens.

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政府社交媒体传播的对话分析:命令和感谢如何引起指责
在重大危机(如 Covid-19 大流行病)期间,政府官员会发布命令以改变人们的行为(如 "待在家里!"),并表达感谢以肯定他人的努力和建立团结。我们利用在 Covid-19 封锁期间英国政府部长在社交媒体上发布的帖子回复的专门数据集,来探讨人们是如何对他们包含指令性言语行为和感谢的信息做出反应的。从经验上看,我们对评价性语言和指责性语言的语料库辅助分析表明,感谢不仅不会促进团队精神,反而会引发至少与指令性语言相同甚至更多的指责性语言。在方法论上,我们展示了如何通过对话分析政府社交媒体交流,以获得有关公民在线反馈的更细致入微的见解。
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来源期刊
Discourse Context & Media
Discourse Context & Media COMMUNICATION-
CiteScore
5.00
自引率
10.00%
发文量
46
审稿时长
55 days
期刊最新文献
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