Towards an Online Risk Mitigation Framework for Political Brands Subject to Computational Propaganda

Abstract

Abstract The influence of computational propaganda on democratic processes globally has necessitated the exploration of mitigation strategies for political brands. The risk associated with computational propaganda includes the spread of misleading information about a political brand over social networking sites through bots (i.e. automated software applications that are programmed to do certain tasks) and newsfeed algorithms at rapid speeds. Apart from bots being used to facilitate the spread of disinformation (i.e. misleading information spread with the intent to manipulate or deceive), human curators also play a role. Research into addressing computational propaganda in the field of political communication is limited, compelling the need to look to consumer brand experts for insight. The current study used semi-structured interviews of senior consumer brand social media practitioners and applied content analysis to develop a framework for mitigating online brand risk associated with computational propaganda for political brands. This computational propaganda brand risk mitigation framework proposes two approaches to curb the effects of computational propaganda, namely, a preventative approach and a recovery approach. Based on established theoretical and practical concepts, this mitigation framework could guide the easing of online brand risk and associated crises for political brands.