Collaborative Research: HCC: Small: Science communication in the ecosystem of digital media platforms

Regents Of The University Of Michigan - Ann Arbor, Ann Arbor MI

Investigators

Abstract

This research will investigate open questions about how scientific advances spread in the ecosystem of digital media platforms. Science communication has undergone dramatic changes over the past decades. Online platforms such as social media sites, electronic news outlets, blogs, and wikis are now used by most scholars and the public for sharing scientific findings. A better understanding of the online circulation of scientific advances is imperative because these new channels of connecting with the public have brought novel challenges in dealing with the uncontrolled distortion of information. Additionally, it remains difficult to identify reliable knowledge, given the increase of sensationalist presentations of scientific results. This work will merge ideas, approaches, and technologies from information science, communication, and journalism to address numerous issues of significant social and economic impact: (1) contributing to the improvement of public serving science journalism; (2) providing practical and actionable early predictions of science dissemination from collective cues on social media; (3) enriching the online experience of people around the globe with a better understanding and tracking of real-world message distortion campaigns; (4) informing key current crises related to misinformation; and, (5) guiding science policy with novel knowledge about science communication in the ecosystem of digital media platforms. While most research on information diffusion has focused on individual platforms, this project will develop a critical multi-platform analysis framework for science communication. A primary goal is to discover fundamental knowledge about: (1) typical trajectories in the cross-platform dissemination of scientific articles, (2) how these trajectories connect to the impact of the work, its novelty, as well as the reactions from scholars and the public, (3) predictions of eventual reactions from early coverage patterns; and, (4) effects of clickbait and information distortion on dissemination. This project will illuminate how scientific findings are shared, discussed, and distorted online and provide empirical evidence of how early signals deduced from social media cues can be harnessed computationally to predict the coverage of scientific articles. The design of an interactive tool will demonstrate how traces of collective reactions can be compellingly and usefully presented to science journalists in real reporting scenarios. The work will be fueled by and will further existing theoretical and empirical research on the use of new media in science dissemination, assess intentional and unintentional information distortion online, harness collective cues from Web-based platforms for early prediction, and design information interfaces for journalists. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.