This work will merge ideas, approaches, and technologies from information science, communication, and journalism to create novel knowledge, advanced models, and an innovative tool that will have broad implications for socially intelligent computing beyond the scope of the proposed research. (1) While the majority of research on information diffusion has focused on individual platforms, this project will develop a critical multi-platform analysis framework for online science communication. (2) It will illuminate how scientific findings are shared, discussed, and distorted online. (3) It will provide empirical evidence of how early signals deduced from collective cues on social media can be harnessed computationally to predict the coverage of scientific articles. (4) It will lead to the design of an interactive tool and 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, intentional and unintentional information distortion online, harnessing collective cues from Web-based platforms for early prediction, and designing information interfaces for journalists.
|Effective start/end date||3/1/22 → 2/28/25|
- National Science Foundation (IIS-2133963)
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