Author: Elena Denia – Polytechnic University of Valencia, Spain
The perception of science is a social aspect studied extensively over the years, nevertheless there exists some criticism about the traditional methodology of questionnaires. The present work takes advantage of the real-time nature of the open data available in the internet, which can provide unexplored dimensions of the public interest in science. In this paper we intend to answer the following research question: what type of information generates more or less interest in the popular scientific discourse? To do so, we focus on Twitter’s public discourse of two science stars –Neil DeGrasse Tyson and Elon Musk– and analyze the content of representative sets of tweets by using data mining techniques, with the purpose of exploring the main concepts that play a key role in terms of laypeople interest. The impact of the information is computed in terms of retweets and likes, and measures of popularity and polemicity of the information are suggested. The study contemplates the weights of different kinds of information classified by categories –science, culture, politics & social, belief, media and emotional– when communicating science, and the results reveal that a transmission of emotional charge awakes a substantially deeper response in the public. We also investigate co-occurrences of words in a semantic network by visual representation to assess the grade of centrality of most attractive concepts, and such a visual analysis of the word network indicates that the peripheral concepts to the scientific discussion show greatest interest, and not the central ones in the discourse. The study is limited to the context of space exploration, therefore it does not answer the generic question about whether science interests, so it is open to a comparison between fields.
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Presentation type: Insight talk