This study examines dynamic communication processes of political misinformation on social media focusing on three components: the temporal pattern, content mutation, and sources of misinformation. We traced the lifecycle of 17 popular political rumors that circulated on Twitter over 13 months during the 2012 U.S. presidential election. Using text analysis based on time series, we found that while false rumors (misinformation) tend to come back multiple times after the initial publication, true rumors (facts) do not. Rumor resurgence continues, often accompanying textual changes, until the tension around the target dissolves. We observed that rumors resurface by partisan news websites that repackage the old rumor into news and, gain visibility by influential Twitter users who introduce such rumor into the Twittersphere. In this paper, we argue that media scholars should consider the mutability of diffusing information, temporal recurrence of such messages, and the mechanism by which these messages evolve over time.

Introduction

Prevalent misinformation online is a growing concern around the globe (WEF, 2014). Whether it is in the form of conspiracy theories or unsubstantiated rumors, false information is now a part of the contemporary media system where varying degrees of information sources vie for our attention. In particular, “fake news,” which generally refers to fabricated news stories purporting to be true, came to the forefront in 2016, circulating wildly during the Brexit vote and the American presidential election. As a result, the Oxford English Dictionary named “posttruth” the 2016 word of the year to highlight less influential role of objective truth in shaping public opinions than political belief or emotion. There has also been considerable research on this topic. Previous research investigated the effects of exposure to false information and corrections on attitudes and political behavior (Cacciatore, Yeo, Scheufele, & Xenos, 2014; Garrett, 2011; Weeks & Garrett, 2014; Berinsky, 2015; Bode & Vraga, 2015; Fridkin, Kenney, & Wintersieck, 2015; Nyhan & Reifler, 2015; Wood & Porter, 2016; Uscinski, Klofstad, & Atkinson, 2017). In general, these studies have found that individuals are more likely to believe in dubious statements that match their partisanship than statements that run counter to their belief (e.g., Weeks, 2015). In addition, some studies reported that corrections usually work in experimental settings where individuals are required to read random debunking messages (e.g., Nyhan & Reifler, 2015), although such efficacy was challenged in a social media environment where people selectively share corrective messages (Shin & Thorson, 2017). Despite growing research in rumors and misinformation, what is largely missing from the current work is dynamic analysis of misinformation diffusion processes online. Scholars argue that misinformation gains its power when it is repeated and passed along from one person to Diffusion of Misinformation 3 another (Bordia & DiFonzo, 2007). That is, the defining characteristics of misinformation are its dynamic mode and collective process that unfolds over time. Therefore, unlike previous studies that examined misinformation as static communication and that take snapshots from experiments or surveys, we focus on changing communicative patterns that occur during the lifecycle of misinformation on social media. Largely exploratory in nature, this study examines a set of questions that shed new light on the nature of political rumoring – and diffusion of information broadly.