An artificial intelligence analysis of climate-change influencers' marketing on Twitter

Abstract

Designing marketing strategies with social media influencers are becoming increasingly relevant for setting political agendas. This study focuses on how two representative social influencers, Greta Thunberg and Bill Gates, engage in advising against climate change. The investigation uses 23,294 tweets posted by them or their followers citing them on climate change around the 25th edition of the United Nations Climate Change Conference. This study applies artificial intelligence and natural language processing to analyse the marketing mechanism of social influencers. We scrutinize the sentiment of the messages and then identify and analyse the different networks constructed around them to discern how pervasive a social influencer's message is. The results show that Thunberg and Gates follow different and unconnected strategies to deliver their messages to their followers.