The impact of science communication on Twitter: The case of Neil deGrasse Tyson




Twitter, communication, science, dissemination, impact, public, participation, computational analysis


Public perceptions of science have been studied extensively since the mid-twentieth century. The aim of this project is to explore the interaction between science and the public in the digital world as a complement to traditional studies on the societal impact of science, particularly on the social network Twitter. It thus proposes a low-cost, easily reproducible methodology involving the design of an algorithm operating on representative sets of tweets to analyse their content by using computational techniques of data mining and natural language processing. To test this methodology, I analyse the communications of the popular science communicator Neil DeGrasse Tyson. The impact of the information is calculated in terms of 1) likes and retweets; 2) suggested formulas for measuring the popularity and controversial nature of the content; and 3) the semantic network. Relevant elements of the communications are then identified and classified according to the categories of “science”, “culture”, “political-social”, “beliefs”, “media” and “emotional”. The results reveal that content with an emotional charge in the communicator’s message triggers a substantially more profound response from the public, as do references to socio-political issues. Moreover, numerous concepts peripheral to the scientific discussion arouse more interest than the concepts central to the communication. Both these results suggest that science is more interesting when it is linked to other issues.