Big data and digital methods in science communication research: opportunities, challenges and limits

Wednesday, June 21, 2017
Resource Type:
Peer-reviewed article | Research Products
Environment Type: 
Media and Technology, Broadcast Media, Websites, Mobile Apps, and Online Media, Comics, Books, and Newspapers, Public Programs, Citizen Science Programs, Exhibitions, Informal/Formal Connections
General Public | Scientists
Computing and information science | Social science and psychology

Computational social science represents an interdisciplinary approach to the study of reality based on advanced computer tools. From economics to political science, from journalism to sociology, digital approaches and techniques for the analysis and management of large quantities of data have now been adopted in several disciplines. The papers in this JCOM commentary focus on the use of such approaches and techniques in the research on science communication. As the papers point out, the most significant advantages of a computational approach in this sector include the chance to open up a range of new research opportunities: from the study of technical and scientific controversies to citizen science, from the definition of new norms and practices for science journalism to open science issues. On the other hand, difficulties are shared with other areas of application. The main risk is that the large quantity of data available can overwhelm the importance of theory. Instead, as the papers in this commentary demonstrate, big data should push scientists to pursue a deeper epistemological and methodological reflection also in the research on science communication.

Publication Name: 
Journal of Science Communication

Team Members

Nico PitrelliNico PitrelliAuthor

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