Internet Rumors During the COVID-19 Pandemic: Dynamics of Topics and Public Psychologies.

Quan Xiao,Shanshan Wan,Xia Li,Xing Zhang,Weiling Huang

doi:10.3389/fpubh.2021.788848

Abstract

The capturing of social opinions, especially rumors, is a crucial issue in digital public health. With the outbreak of the COVID-19 pandemic, the discussions of related topics have increased exponentially in social media, with a large number of rumors on the Internet, which highly impede the harmony and sustainable development of society. As human health has never suffered a threat of this magnitude since the Internet era, past studies have lacked in-depth analysis of rumors regarding such a globally sweeping pandemic. This text-based analysis explores the dynamic features of Internet rumors during the COVID-19 pandemic considering the progress of the pandemic as time-series. Specifically, a Latent Dirichlet Allocation (LDA) model is used to extract rumor topics that spread widely during the pandemic, and the extracted six rumor topics, i.e., “Human Immunity,” “Technology R&D,” “Virus Protection,” “People's Livelihood,” “Virus Spreading,” and “Psychosomatic Health” are found to show a certain degree of concentrated distribution at different stages of the pandemic. Linguistic Inquiry and Word Count (LIWC) is used to statistically test the psychosocial dynamics reflected in the rumor texts, and the results show differences in psychosocial characteristics of rumors at different stages of the pandemic progression. There are also differences in the indicators of psychosocial characteristics between truth and disinformation. Our results reveal which topics of rumors and which psychosocial characteristics are more likely to spread at each stage of progress of the pandemic. The findings contribute to a comprehensive understanding of the changing public opinions and psychological dynamics during the pandemic, and also provide reference for public opinion responses to major public health emergencies that may arise in the future.

Highlights

The monitoring and analysis of public opinions is an important task for modern society, as they may provide critical information that enables the timely capture of unanticipated public hotspots and trends, contributing to government business continuity [1]
The current study addresses the following research questions (RQs): RQ1: During the COVID-19 pandemic, what types of Internet rumors were widely circulated? RQ2: How have public concerns presented by the topic of Internet rumors changed across different stages of the pandemic? RQ3: What kind of psychosocial characteristics were implied in these Internet rumors and how did they differ during different stages as the pandemic evolved?
The popular rumor topics are mined by performing Latent Dirichlet Allocation (LDA) topic modeling, and the psychosocial characteristics inherent in the rumors are captured based on the Linguistic Inquiry and Word Count (LIWC) metrics

Summary

Introduction

The monitoring and analysis of public opinions is an important task for modern society, as they may provide critical information that enables the timely capture of unanticipated public hotspots and trends, contributing to government business continuity [1]. Out of the public’s fear of the unknown, Internet rumors have been emerging in various aspects including viruses, health, and livelihoods: from “drinking soda to prevent new coronaviruses,” to “China banning the export of face masks,” to “playing in the snow to catch new coronaviruses” [9]. These rumors, a large proportion of which may be misinformation, exacerbated the public’s physiological over-reaction to the unknown viruses and their psychological fears [10, 11]. Besides the public health impact, the psychosocial offshoots have been significant [12]

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Conclusion