Exploring how online responses change in response to debunking messages about COVID-19 on WhatsApp

Abstract

PurposeThe COVID-19 pandemic has spurred a concurrent outbreak of false information online. Debunking false information about a health crisis is critical as misinformation can trigger protests or panic, which necessitates a better understanding of it. This exploratory study examined the effects of debunking messages on a COVID-19-related public chat on WhatsApp in Singapore.Design/methodology/approachTo understand the effects of debunking messages about COVID-19 on WhatsApp conversations, the following was studied. The relationship between source credibility (i.e. characteristics of a communicator that affect the receiver's acceptance of the message) of different debunking message types and their effects on the length of the conversation, sentiments towards various aspects of a crisis, and the information distortions in a message thread were studied. Deep learning techniques, knowledge graphs (KG), and content analyses were used to perform aspect-based sentiment analysis (ABSA) of the messages and measure information distortion.FindingsDebunking messages with higher source credibility (e.g. providing evidence from authoritative sources like health authorities) help close a discussion thread earlier. Shifts in sentiments towards some aspects of the crisis highlight the value of ABSA in monitoring the effectiveness of debunking messages. Finally, debunking messages with lower source credibility (e.g. stating that the information is false without any substantiation) are likely to increase information distortion in conversation threads.Originality/valueThe study supports the importance of source credibility in debunking and an ABSA approach in analysing the effect of debunking messages during a health crisis, which have practical value for public agencies during a health crisis. Studying differences in the source credibility of debunking messages on WhatsApp is a novel shift from the existing approaches. Additionally, a novel approach to measuring information distortion using KGs was used to shed insights on how debunking can reduce information distortions.

An experimental study of the effectiveness of fact checks: interplay of evidence type, veracity and news agreement

“…For instance, Young et al (2018) found that fact checks presented as videos with narration were more efficient than print for changing readers' beliefs, and the inclusion of humor did not play a role in influencing policy evaluations. Chen et al (2022) found that debunking messages with more authoritative sources were able to lower the possibility of information distortion by ending a discussion thread quicker on WhatsApp. Moreover, Fridkin et al (2015) found that negative fact checks disputing the claims of a commercial were more robust than positive fact checks agreeing with the claims.…”

“…(2018) found that fact checks presented as videos with narration were more efficient than print for changing readers' beliefs, and the inclusion of humor did not play a role in influencing policy evaluations. Chen et al . (2022) found that debunking messages with more authoritative sources were able to lower the possibility of information distortion by ending a discussion thread quicker on WhatsApp.…”

“Masks do not work”: COVID-19 misperceptions and theory-driven corrective strategies on Facebook

“…So far, much research on misinformation correction has studied the influence of source credibility (e.g. Chen et al, 2022;Van der Meer and Jin, 2019), but not so much on message credibility. Message credibility, however, is closely connected to source credibility (Slater and Rouner, 1996) and when improved, can be one of the factors that lead to reducing misperceptions (Kim et al, 2020;Vraga et al, 2019).…”

Evaluating the elevation of authoritative health content online during the COVID-19 pandemic

“…"Trust in social media" is therefore generally reflective of our beliefs about, and trust towards, the actors who control that technology (Deley and Dubois, 2020). Conspiracy theories, misinformation and disinformation have proliferated online prior to, and during, the COVID-19 pandemic (Chen et al, 2022). Digital technologies not only make harmful information more accessible, misinformation can now be created and amplified at an unprecedented speed and scale (Baker et al, 2020;Cifuentes-Faura, 2021).…”

“…“Trust in social media” is therefore generally reflective of our beliefs about, and trust towards, the actors who control that technology (Deley and Dubois, 2020). Conspiracy theories, misinformation and disinformation have proliferated online prior to, and during, the COVID-19 pandemic (Chen et al. , 2022).…”