2022
DOI: 10.1145/3555542
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From Crowd Ratings to Predictive Models of Newsworthiness to Support Science Journalism

Abstract: The scale of scientific publishing continues to grow, creating overload on science journalists who are inundated with choices for what would be most interesting, important, and newsworthy to cover in their reporting. Our work addresses this problem by considering the viability of creating a predictive model of newsworthiness of scientific articles that is trained using crowdsourced evaluations of newsworthiness. We proceed by first evaluating the potential of crowd-sourced evaluations of newsworthiness by asse… Show more

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Cited by 4 publications
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References 42 publications
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