Identifying and characterizing public science‐related fears from RSS feeds

Mike A Thelwall · Rudy Prabowo

23 citations0/0 files storedJournal of the American Society for Information Science and Technology

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Computational and Text Analysis Methods Misinformation and Its Impacts Sentiment Analysis and Opinion Mining

Abstract

Abstract A feature of modern democracies is public mistrust of scientists and the politicization of science policy, e.g., concerning stem cell research and genetically modified food. While the extent of this mistrust is debatable, its political influence is tangible. Hence, science policy researchers and science policy makers need early warning of issues that resonate with a wide public so that they can make timely and informed decisions. In this article, a semi‐automatic method for identifying significant public science‐related concerns from a corpus of Internet‐based RSS (Really Simple Syndication) feeds is described and shown to be an improvement on a previous similar system because of the introduction of feed‐based aggregation. In addition, both the RSS corpus and the concept of public science‐related fears are deconstructed, revealing hidden complexity. This article also provides evidence that genetically modified organisms and stem cell research were the two major policy‐relevant science concern issues, although mobile phone radiation and software security also generated significant interest.

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