This article examines certain guiding tenets of science journalism in the era of big data by focusing on its engagement with citizen science. Having placed citizen science in historical context, it highlights early interventions intended to help establish the basis for an alternative epistemological ethos recognising the scientist as citizen and the citizen as scientist. Next, the article assesses further implications for science journalism by examining the challenges posed by big data in the realm of citizen science. Pertinent issues include potential risks associated with data quality
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
In this book, Brian G. Southwell discusses how disparities in information-sharing arise and what can be done to alleviate them. In all sorts of ways and for all sorts of reasons, people have always sought to share information among their family and other social networks. However, this sharing has never been equal: inevitably, some people are better-informed than others and some are more socially-connected than others. At first glance, the plethora of communication tools and technologies available nowadays should help democratise information and reduce disparity but differences in how, when and