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Date: | Fri, 12 Mar 2021 12:30:26 -0500 |
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> is there a taint of bias, and were the underlying data sufficiently comparable for the distributions and curves assumed, etc. etc. ?
Recent article:
> Our findings suggest a person’s trust in online information and perceived information overload are strong predictors of unverified information sharing. Furthermore, these factors, along with a person’s perceived COVID-19 severity and vulnerability influence cyberchondria. Females were significantly more likely to suffer from cyberchondria, with males more likely to share news without verifying its reliability.
> The first step is to understand why people share unverified COVID-19 related information through social media. ... Sharing unverified information is mostly motivated by social reasons, to inform others and to self-express. 18,7% of people who share information are motivated by upsetting others.
What drives unverified information sharing and cyberchondria during the COVID-19 pandemic? EUROPEAN JOURNAL OF INFORMATION SYSTEMS2020, VOL. 29, NO. 3, 288-305
PLB
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