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.

View More Papers

A Robust Counting Sketch for Data Plane Intrusion Detection

Sian Kim (Ewha Womans University), Changhun Jung (Ewha Womans University), RhongHo Jang (Wayne State University), David Mohaisen (University of Central Florida), DaeHun Nyang (Ewha Womans University)

Read More

Location Spoofing Attacks on Autonomous Fleets

Jinghan Yang, Andew Estornell, Yevgeniy Vorobeychik (Washington University in St. Louis)

Read More

Reconciling the Hacker Spirit

Yan Shoshitaishvili (Arizona State University)

Read More

Accurate Compiler and Optimization Independent Function Identification Using Program...

Derrick McKee (Purdue University), Nathan Burow (MIT Lincoln Laboratory), Mathias Payer (EPFL)

Read More