Filipo Sharevski (DePaul University), Amy Devine (DePaul University), Emma Pieroni (DePaul University), Peter Jachim (DePaul University)

In this paper we investigate what textit{folk models of misinformation} exist on social media with a sample of 235 social media users. Work on social media misinformation does not investigate how ordinary users deal with it; rather, the focus is mostly on the anxiety, tensions, or divisions misinformation creates. Studying only the structural aspects also overlooks how misinformation is internalized by users on social media and thus is quick to prescribe "inoculation" strategies for the presumed lack of immunity to misinformation. How users grapple with social media content to develop "natural immunity" as a precursor to misinformation resilience, however, remains an open question. We have identified at least five textit{folk models} that conceptualize misinformation as either: textit{political (counter)argumentation}, textit{out-of-context narratives}, textit{inherently fallacious information}, textit{external propaganda}, or simply textit{entertainment}. We use the rich conceptualizations embodied in these folk models to uncover how social media users minimize adverse reactions to misinformation encounters in their everyday lives.

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Noah T. Curran (University of Michigan), Kang G. Shin (University of Michigan), William Hass (Lear Corporation), Lars Wolleschensky (Lear Corporation), Rekha Singoria (Lear Corporation), Isaac Snellgrove (Lear Corporation), Ran Tao (Lear Corporation)

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Bishakh Chandra Ghosh (Indian Institute of Technology Kharagpur), Sikhar Patranabis (IBM Research - India), Dhinakaran Vinayagamurthy (IBM Research - India), Venkatraman Ramakrishna (IBM Research - India), Krishnasuri Narayanam (IBM Research - India), Sandip Chakraborty (Indian Institute of Technology Kharagpur)

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Ke Sun (University of California San Diego), Chunyu Xia (University of California San Diego), Songlin Xu (University of California San Diego), Xinyu Zhang (University of California San Diego)

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