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.

The effect of green influencer message characteristics: Framing, construal, and timing

“…Second, we provide an overview of the communication practices of 1000 green influencers with strongly varying follower numbers (nano, micro, and macro by follower number), where extant content analyses focused on selected green macroinfluencers (i.e., Bill Gates and Greta Thunberg: Ballestar et al, 2022). We find that the different framing approaches that extant research documents also exist in a wider sample of green influencers—although the positive gain frames dominate here.…”

“…e.g., we'll never recycle our way out of our #plasticpollution crisis […].” by @green4ema). While most greenfluencers use gain framing (Townsend, 2022), there are examples of loss framing, such as the activist and influencer Greta Thunberg, who mainly uses negative sentiments and words (e.g., “climate crisis”: Ballestar et al, 2022). To the best of our knowledge, no studies to date investigate the effect of message framing in green influencer messages.…”

The power of flattery: Enhancing prosocial behavior through virtual influencers

“…The experimental design is selected for its unique ability to establish causal relationships, allowing for controlled manipulation of variables and rigorous testing of hypotheses. In comparison, existing studies employ diverse methods such as text analysis (Arsenyan & Mirowska, 2021), in‐depth interviews (Miao et al, 2022; Mrad et al, 2022), opinion mining and sentiment analysis (Ballestar et al, 2022), and online surveys (Ahn et al, 2022). While these methods are valuable in exploring specific aspects of VIs, they lack the experimental control necessary for causal inference.…”

Investigating the effectiveness of virtual influencers in prosocial marketing

“…Social media influencers are “individuals who have accrued a sizable and engaged following on one or more social media platforms, and who possess the power to shape attitudes, opinions, and behaviors of their audience through their online content” (Freberg et al, 2011, p. 90). Recently, research has increasingly been exploring influencers' potential for altering consumers' behavior in prosocial contexts (Ballestar et al, 2022; Pittman & Abell, 2021; Zhang et al, 2021). Studies have found that congruency between influencers' identity (race and image) as well as the congruency between an influencer's image and proenvironmental message plays an important role in shaping an influencer's credibility and driving followers' engagement (Boerman et al, 2022; Yang et al, 2021).…”