Tracking Private WhatsApp Discourse About COVID-19 in Singapore: Longitudinal Infodemiology Study

Edina Yq Tan, Russell Re Wee, Young Ern Saw, Kylie Jq Heng, Joseph We Chin, Eddie Mw Tong, Jean Cj Liu, Edina Yq Tan, Russell Re Wee, Young Ern Saw, Kylie Jq Heng, Joseph We Chin, Eddie Mw Tong, Jean Cj Liu

Abstract

Background: Worldwide, social media traffic increased following the onset of the COVID-19 pandemic. Although the spread of COVID-19 content has been described for several social media platforms (eg, Twitter and Facebook), little is known about how such content is spread via private messaging platforms, such as WhatsApp (WhatsApp LLC).

Objective: In this study, we documented (1) how WhatsApp is used to transmit COVID-19 content, (2) the characteristics of WhatsApp users based on their usage patterns, and (3) how usage patterns link to COVID-19 concerns.

Methods: We used the experience sampling method to track day-to-day WhatsApp usage during the COVID-19 pandemic. For 1 week, participants reported each day the extent to which they had received, forwarded, or discussed COVID-19 content. The final data set comprised 924 data points, which were collected from 151 participants.

Results: During the weeklong monitoring process, most participants (143/151, 94.7%) reported at least 1 COVID-19-related use of WhatsApp. When a taxonomy was generated based on usage patterns, around 1 in 10 participants (21/151, 13.9%) were found to have received and shared a high volume of forwarded COVID-19 content, akin to super-spreaders identified on other social media platforms. Finally, those who engaged with more COVID-19 content in their personal chats were more likely to report having COVID-19-related thoughts throughout the day.

Conclusions: Our findings provide a rare window into discourse on private messaging platforms. Such data can be used to inform risk communication strategies during the pandemic.

Trial registration: ClinicalTrials.gov NCT04367363; https://ichgcp.net/clinical-trials-registry/NCT04367363.

Keywords: COVID-19; Singapore; WhatsApp; app; characteristic; communication; infodemiology; longitudinal; misinformation; pattern; risk; social media; surveillance; tracking; usage; well-being.

Conflict of interest statement

Conflicts of Interest: None declared.

©Edina YQ Tan, Russell RE Wee, Young Ern Saw, Kylie JQ Heng, Joseph WE Chin, Eddie MW Tong, Jean CJ Liu. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 23.12.2021.

Figures

Figure 1
Figure 1
Schematic of study procedures. All participants completed a baseline questionnaire. This was followed by 7 days of experience sampling, during which participants addressed questions about COVID-19 concerns and WhatsApp usage daily. Participants completed a final questionnaire 1 day after the experience sampling procedure ended. DASS-21: 21-item Depression, Anxiety and Stress Scale.
Figure 2
Figure 2
Distribution of COVID-19–related behaviors on WhatsApp. In a weeklong experience sampling procedure, participants reported the extent to which they engaged in COVID-19–related behaviors on WhatsApp (either by forwarding or receiving messages or in conversations). Horizontal bars represent the total amount of each activity captured (averaged across all participants). Horizontal lines represent the 95% CIs for the means.
Figure 3
Figure 3
Sources of COVID-19 news. In a questionnaire, participants self-reported the sources from which they received COVID-19 news.
Figure 4
Figure 4
Taxonomy of COVID-19–related WhatsApp usage. By using latent profile analysis, we classified participants based on how they had used WhatsApp to engage with COVID-19 content during 1 week of monitoring. The figure depicts the WhatsApp usage activities of chronic users (top left), receiving users (top right), discursive users (bottom left), and minimal users (bottom right). Horizontal lines represent the 95% CIs for the means.
Figure 5
Figure 5
Classification tree analysis. Recursive partitioning was used to predict which of the four WhatsApp usage profiles (chronic, receiving, discursive, or minimal) participants belonged to based on baseline questionnaire measures (demographics; COVID-19 concerns; scores on the 21-item Depression, Anxiety and Stress Scale; and time of WhatsApp usage). The final tree model is presented as a flowchart; factors are chosen at each level to categorize the maximal number of participants. Marital status, the time of WhatsApp usage, and age emerged as the primary predictors (model classification accuracy: 64.2%; above the chance level of 25%).
Figure 6
Figure 6
COVID-19–related thoughts and fears over 1 week. Day-to-day variations in COVID-19–related thought (top) and fear levels (bottom) as a function of WhatsApp user profiles. The shaded grey areas represent 95% CIs.

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