🤖 AI Summary
This study addresses a critical yet underexplored phenomenon in community governance: the perception that others’ information is false—termed “perceived misinformation”—which undermines trust and democratic deliberation even in the absence of objectively verifiable falsehoods. Drawing on a qualitative case study of community conflict triggered by a casino proposal, the paper introduces and rigorously defines “perceived misinformation,” clearly distinguishing it from objective misinformation and thereby expanding the theoretical boundaries of misinformation research. Integrating sociological and communication frameworks, the analysis elucidates how this perception emerges and intensifies amid governance dysfunction, communicative breakdowns, and discursive polarization. The study further proposes mechanisms for identifying such perceptions, pathways for relational repair, and targeted intervention designs, offering both theoretical insights and practical strategies to mitigate their corrosive effects on community democracy.
📝 Abstract
During community decision-making and civic collaboration, conflicts can escalate when people suspect misinformation. We introduce the concept of sense of misinformation as experiencing someone's language or behavior as misinformation when it is not, that is to say when no falsehood is involved. Misinformation and sense of misinformation feel similar and can have similar social consequences; but sense of misinformation rests upon a mistaken perception of someone else's information as false. Through a case study of a casino proposal in local community, we examine how sense of misinformation developed over time during a contentious civic process through key factors (i.e., miscoordination governance, miscommunication between local government and citizens, and conflict and the breakdown of civic discourse), undermining trust and community democracy. Distinguishing between misinformation and sense of misinformation presents a challenge, but it is important. We contribute a conceptual distinction to the misinformation literature by identifying this distinct phenomenon and discuss ways to help communities recognize and repair such misattributions. Finally, we discuss design approaches for mitigating sense of misinformation.