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Climate change denial on Twitter: identifying attributes

Along with raised importance of climate change topic, the “denial machine and its campaign” (Dunlap, 2013, p. 692) are getting more public attention as well. This thesis aims to analyze denial communication on Twitter, as it is often utilized to communicate social and political issues and gathering information about climate change-related topics (Segerberg & Bennett, 2011; Giglietto, Rossi, & Bennato, 2012). The thesis addresses following research questions: (1) Which attributes of climate change denial exist on Twitter? (2) Are there differences in the presence of certain attributes in the tweets with and without specific denial hashtag? (3) Which climate change denial attributes lead to the widest social media interaction?

To approach the listed above research questions, Entman’s (1993) framing model is utilized. It includes problem definition, diagnosing causes, moral evaluation, and suggestion of the remedies, which are completed by the inductively and deductively detected attributes (sub-framing elements). This study uses manual content analysis as the leading method, while automatic keywords extraction was utilized in the first parts of the research. Analysis was performed on the sample size of 1050 tweets equally distributed among #climatechange, #climatechangehoax, #globalwarming hashtags. The data is retrieved from Climate Change Tweets Ids Harvard Dataset.

The results show the presence of the problem, the moral evaluation of climate change activists and hostile political powers, negative consequences and financial remedies among the most frequently occurring. As a framing element, moral evaluation is leading, present in 60% of the tweets. Problem definition is most occurring in #globalwarming data (41%) while anthropogenic and natural causes are the most present in #climatechange (20.3% and 18.9%) data. No influence of content of the attributes on social media interaction was found. Climate change denial communication is a rarely addressed in academic topics. However, the results of presence denial attributes on Twitter show the same trends which are observed in traditional media. Low social media interaction is explained by the fact, that denial point of view regarding climate change is less likely to be discussed in public (Ballew et al., 2019).