What is going on? An evidence-frame framework for analyzing online rumors about election integrity

Pervasive falsehoods that erode trust in election processes are of increasing concern to democracies around the world. Misleading claims like these are often understood as simply “getting the facts wrong”. Using a grounded, interpretative, mixed-method approach to study Twitter activity during the 2022 U.S. Midterm Election in Arizona, our work paints a more nuanced picture. We adapt Klein’s \cite{klein_data-frame_2007} data-frame theory of collective sensemaking to online rumors, demonstrating how misleading claims about election administration take shape online through interactions between (often factual) evidence and frames. We introduce a methodological approach for analyzing rumors through this evidence-frame lens and provide insights into the dynamics of online rumoring around claims of "rigged elections". Our work highlights how rumors are as much about political framing as they are about faulty facts, and locates the crux of the problem of misinformation in the interactions with and between evidence and distorted political frames.