scholarly journals COVID-19 Scientific Facts Vs. Conspiracy Theories: 0 – 1: Science Fails to Convince Even Highly Educated Individuals

2020 ◽  
Author(s):  
Marios Constantinou ◽  
Anthony Kagialis ◽  
Maria Karekla

Abstract Science may be failing to convince a significant number of people about COVID-19 scientific facts and needed public health measures. Individual and social factors are behind believing conspiracy theories. Adults (N = 1001) were asked to rate their beliefs in various conspiracy theories circulating in social media, rate their psychological distress relating to COVID-19, rate their trust in science to solve COVID-19 problems, and rate their willingness to adhere to measures regarding social distancing and quarantine. The findings showed conspiracy theories are widely believed even among highly educated individuals. Stronger conspiracy theory beliefs predicted science mistrust and unwillingness to adhere to public health measures. Psychological distress increased conspiracy beliefs. Recommendations, stemming from the findings, for reducing such beliefs and better serve public health are discussed.

Author(s):  
Marios Constantinou ◽  
Antonios Kagialis ◽  
Maria Karekla

Science may be failing to convince a significant number of people about COVID-19 scientific facts and needed public health measures. Individual and social factors are behind believing conspiracy theories. Adults (N = 1001) were asked to rate their beliefs in various conspiracy theories circulating in social media, rate their psychological distress relating to COVID-19, rate their trust in science to solve COVID-19 problems, and rate their willingness to adhere to measures regarding social distancing and quarantine. The findings showed conspiracy theories are widely believed and related to lower age, lower education, living in less densely populated areas, and lower income. Stronger conspiracy theory beliefs predicted science mistrust and unwillingness to adhere to public health measures. Psychological state was a strong predictor of conspiracy beliefs. Recommendations, stemming from the findings, for reducing such beliefs and better serving public health are discussed.


2021 ◽  
Author(s):  
Ikpe Justice Akpan ◽  
Obianuju Genevieve Aguolu ◽  
Yawo Mamoua Kobara ◽  
Rouzbeh Razavi ◽  
Asuama A Akpan ◽  
...  

BACKGROUND The use of the internet and web-based platforms to obtain public health information and manage health-related issues has become widespread in this digital age. The practice is so pervasive that the first reaction to obtaining health information is to “Google it.” As SARS-CoV-2 broke out in Wuhan, China, in December 2019 and quickly spread worldwide, people flocked to the internet to learn about the novel coronavirus and the disease, COVID-19. Lagging responses by governments and public health agencies to prioritize the dissemination of information about the coronavirus outbreak through the internet and the World Wide Web and to build trust gave room for others to quickly populate social media, online blogs, news outlets, and websites with misinformation and conspiracy theories about the COVID-19 pandemic, resulting in people’s deviant behaviors toward public health safety measures. OBJECTIVE The goals of this study were to determine what people learned about the COVID-19 pandemic through web searches, examine any association between what people learned about COVID-19 and behavior toward public health guidelines, and analyze the impact of misinformation and conspiracy theories about the COVID-19 pandemic on people’s behavior toward public health measures. METHODS This infodemiology study used Google Trends’ worldwide search index, covering the first 6 months after the SARS-CoV-2 outbreak (January 1 to June 30, 2020) when the public scrambled for information about the pandemic. Data analysis employed statistical trends, correlation and regression, principal component analysis (PCA), and predictive models. RESULTS The PCA identified two latent variables comprising past coronavirus epidemics (pastCoVepidemics: keywords that address previous epidemics) and the ongoing COVID-19 pandemic (presCoVpandemic: keywords that explain the ongoing pandemic). Both principal components were used significantly to learn about SARS-CoV-2 and COVID-19 and explained 88.78% of the variability. Three principal components fuelled misinformation about COVID-19: misinformation (keywords “biological weapon,” “virus hoax,” “common cold,” “COVID-19 hoax,” and “China virus”), conspiracy theory 1 (ConspTheory1; keyword “5G” or “@5G”), and conspiracy theory 2 (ConspTheory2; keyword “ingest bleach”). These principal components explained 84.85% of the variability. The principal components represent two measurements of public health safety guidelines—public health measures 1 (PubHealthMes1; keywords “social distancing,” “wash hands,” “isolation,” and “quarantine”) and public health measures 2 (PubHealthMes2; keyword “wear mask”)—which explained 84.7% of the variability. Based on the PCA results and the log-linear and predictive models, ConspTheory1 (keyword “@5G”) was identified as a predictor of people’s behavior toward public health measures (PubHealthMes2). Although correlations of misinformation (keywords “COVID-19,” “hoax,” “virus hoax,” “common cold,” and more) and ConspTheory2 (keyword “ingest bleach”) with PubHealthMes1 (keywords “social distancing,” “hand wash,” “isolation,” and more) were <i>r</i>=0.83 and <i>r</i>=–0.11, respectively, neither was statistically significant (<i>P</i>=.27 and <i>P</i>=.13, respectively). CONCLUSIONS Several studies focused on the impacts of social media and related platforms on the spreading of misinformation and conspiracy theories. This study provides the first empirical evidence to the mainly anecdotal discourse on the use of web searches to learn about SARS-CoV-2 and COVID-19.


10.2196/26527 ◽  
2021 ◽  
Vol 7 (4) ◽  
pp. e26527
Author(s):  
Dax Gerts ◽  
Courtney D Shelley ◽  
Nidhi Parikh ◽  
Travis Pitts ◽  
Chrysm Watson Ross ◽  
...  

Background The COVID-19 outbreak has left many people isolated within their homes; these people are turning to social media for news and social connection, which leaves them vulnerable to believing and sharing misinformation. Health-related misinformation threatens adherence to public health messaging, and monitoring its spread on social media is critical to understanding the evolution of ideas that have potentially negative public health impacts. Objective The aim of this study is to use Twitter data to explore methods to characterize and classify four COVID-19 conspiracy theories and to provide context for each of these conspiracy theories through the first 5 months of the pandemic. Methods We began with a corpus of COVID-19 tweets (approximately 120 million) spanning late January to early May 2020. We first filtered tweets using regular expressions (n=1.8 million) and used random forest classification models to identify tweets related to four conspiracy theories. Our classified data sets were then used in downstream sentiment analysis and dynamic topic modeling to characterize the linguistic features of COVID-19 conspiracy theories as they evolve over time. Results Analysis using model-labeled data was beneficial for increasing the proportion of data matching misinformation indicators. Random forest classifier metrics varied across the four conspiracy theories considered (F1 scores between 0.347 and 0.857); this performance increased as the given conspiracy theory was more narrowly defined. We showed that misinformation tweets demonstrate more negative sentiment when compared to nonmisinformation tweets and that theories evolve over time, incorporating details from unrelated conspiracy theories as well as real-world events. Conclusions Although we focus here on health-related misinformation, this combination of approaches is not specific to public health and is valuable for characterizing misinformation in general, which is an important first step in creating targeted messaging to counteract its spread. Initial messaging should aim to preempt generalized misinformation before it becomes widespread, while later messaging will need to target evolving conspiracy theories and the new facets of each as they become incorporated.


Author(s):  
Ashli Au

Have you heard? In today’s pandemic, the Trudeau administration has been using the widespread lockdowns to impose socialism in Canada. This conspiracy theory has been mobilized under the hash tags #StopTheGreatReset, #Scamdemic and #CancelTheLockdown amongst others. With the COVID-19 pandemic, as with previous major events, there has been an influx of dis-and mis- information on social media platforms. This rapid spread of information can have strong influences on people’s behaviour which can impact the effectiveness of public health measures taken by governments (Cinelli et al. 2020; González-Padilla andTortolero-Blanco 2020). My research is part of an ongoing project that aims to identify and map the spread of  disinformation, and its effects on Canadian society. For this sub-project, I created a database of social media posts from Twitter accounts that promote or spread disinformation narratives directed towards Canadian politics and public health measures. From this, we were able to identify some of the most common narratives of disinformation in circulation on Twitter; the hash tag #StopTheGreatReset was chosen as the focus of the project to study the fine, and often blurred, line between legitimate politics and conspiracy theories. Going forth, my aim is to conduct a qualitative analysis on the links attached to social media posts fueling disinformation to understand what kinds of information are being circulated and identify common themes. This project has been an opportunity for me to learn about how social media research is conducted and allows me to engage with urgent issues in contemporary media culture.


2020 ◽  
Vol 1 (2) ◽  
pp. 36-39
Author(s):  
Andreas Goreis ◽  
Oswald D. Kothgassner

Highlights: Conspiracy beliefs are spread via social media platforms and may have a negative impact on preventive health measures Preventive measures against fear and misinformation need to consider the differential effects of different forms of conspiracy theories on behavior Fostering awareness in society about COVID-19 misinformation in social media is crucial.


2021 ◽  
pp. 096366252199802
Author(s):  
Xizhu Xiao ◽  
Porismita Borah ◽  
Yan Su

Since the beginning of the COVID-19 pandemic, misinformation has been circulating on social media and multiple conspiracy theories have since become quite popular. We conducted a U.S. national survey for three main purposes. First, we aim to examine the association between social media news consumption and conspiracy beliefs specific to COVID-19 and general conspiracy beliefs. Second, we investigate the influence of an important moderator, social media news trust, that has been overlooked in prior studies. Third, we further propose a moderated moderation model by including misinformation identification. Our findings show that social media news use was associated with higher conspiracy beliefs, and trust in social media news was found to be a significant moderator of the relationship between social media news use and conspiracy beliefs. Moreover, our findings show that misinformation identification moderated the relationship between social media news use and trust. Implications are discussed.


2020 ◽  
Author(s):  
Daisy Massey ◽  
Chenxi Huang ◽  
Yuan Lu ◽  
Alina Cohen ◽  
Yahel Oren ◽  
...  

BACKGROUND The coronavirus disease 2019 (COVID-19) has continued to spread in the US and globally. Closely monitoring public engagement and perception of COVID-19 and preventive measures using social media data could provide important information for understanding the progress of current interventions and planning future programs. OBJECTIVE To measure the public’s behaviors and perceptions regarding COVID-19 and its daily life effects during the recent 5 months of the pandemic. METHODS Natural language processing (NLP) algorithms were used to identify COVID-19 related and unrelated topics in over 300 million online data sources from June 15 to November 15, 2020. Posts in the sample were geotagged, and sensitivity and specificity were both calculated to validate the classification of posts. The prevalence of discussion regarding these topics was measured over this time period and compared to daily case rates in the US. RESULTS The final sample size included 9,065,733 posts, 70% of which were sourced from the US. In October and November, discussion including mentions of COVID-19 and related health behaviors did not increase as it had from June to September, despite an increase in COVID-19 daily cases in the US beginning in October. Additionally, counter to reports from March and April, discussion was more focused on daily life topics (69%), compared with COVID-19 in general (37%) and COVID-19 public health measures (20%). CONCLUSIONS There was a decline in COVID-19-related social media discussion sourced mainly from the US, even as COVID-19 cases in the US have increased to the highest rate since the beginning of the pandemic. Targeted public health messaging may be needed to ensure engagement in public health prevention measures until a vaccine is widely available to the public.


Comunicar ◽  
2021 ◽  
Vol 29 (69) ◽  
Author(s):  
Tianru Guan ◽  
Tianyang Liu ◽  
Randong Yuan

Among the burgeoning discussions on the argumentative styles of conspiracy theories and the related cognitive processes of their audiences, research thus far is limited in regard to developing methods and strategies that could effectively debunk conspiracy theories and reduce the harmful influences of conspiracist media exposure. The present study critically evaluates the effectiveness of five approaches to reducing conspiratorial belief, through experiments (N=607) conducted on Amazon Mechanical Turk. Our results demonstrate that the content-based methods of counter conspiracy theory can partly mitigate conspiratorial belief. Specifically, the science- and fact-focused corrections were able to effectively mitigate conspiracy beliefs, whereas media literacy and inoculation strategies did not produce significant change. More crucially, our findings illustrate that both audience-focused methods, which involve decoding the myth of conspiracy theory and re-imagining intergroup relationships, were effective in reducing the cognitive acceptance of conspiracy theory. Building on these insights, this study contributes to a systematic examination of different epistemic means to influence (or not) conspiracy beliefs -an urgent task in the face of the infodemic threat apparent both during and after the COVID-19 pandemic. Entre las crecientes discusiones sobre los estilos argumentativos de las teorías de conspiración y los procesos cognitivos relacionados de su público, los estudios hasta ahora son limitados en lo que respecta al desarrollo de métodos y estrategias que podrían desacreditar eficazmente las teorías de conspiración y reducir las influencias dañinas de la exposición a los medios de comunicación conspirativos. El presente estudio evalúa de manera crítica la efectividad de cinco enfoques para reducir la creencia en conspiraciones, a través de experimentos (N=607) realizados en Amazon Mechanical Turk. Nuestros resultados demuestran que los métodos basados en el contenido al enfrentar las teorías de la conspiración pueden mitigar parcialmente la creencia conspiratoria. Específicamente, las correcciones centradas en la ciencia y los hechos fueron capaces de mitigar eficazmente las creencias en la conspiración, mientras que las estrategias de alfabetización mediática e inoculación no produjeron cambios significativos. Más importante aún, nuestros hallazgos ilustran que ambos métodos centrados en el público, que implican decodificar el mito de la teoría de la conspiración y reimaginar las relaciones intergrupales, fueron efectivos para reducir la aceptación cognitiva de la teoría de la conspiración. Basado en estos conocimientos, este estudio contribuye a un examen sistemático de distintos medios epistemológicos para influir (o no) en las creencias conspirativas, una tarea urgente frente a la evidente amenaza infodémica, tanto durante como después de la pandemia de COVID-19.


2020 ◽  
Author(s):  
Wasim Ahmed ◽  
Francesc López Seguí ◽  
Josep Vidal-Alaball ◽  
Matthew S Katz

BACKGROUND During the COVID-19 pandemic, a number of conspiracy theories have emerged. A popular theory posits that the pandemic is a hoax and suggests that certain hospitals are “empty.” Research has shown that accepting conspiracy theories increases the likelihood that an individual may ignore government advice about social distancing and other public health interventions. Due to the possibility of a second wave and future pandemics, it is important to gain an understanding of the drivers of misinformation and strategies to mitigate it. OBJECTIVE This study set out to evaluate the #FilmYourHospital conspiracy theory on Twitter, attempting to understand the drivers behind it. More specifically, the objectives were to determine which online sources of information were used as evidence to support the theory, the ratio of automated to organic accounts in the network, and what lessons can be learned to mitigate the spread of such a conspiracy theory in the future. METHODS Twitter data related to the #FilmYourHospital hashtag were retrieved and analyzed using social network analysis across a 7-day period from April 13-20, 2020. The data set consisted of 22,785 tweets and 11,333 Twitter users. The Botometer tool was used to identify accounts with a higher probability of being bots. RESULTS The most important drivers of the conspiracy theory are ordinary citizens; one of the most influential accounts is a Brexit supporter. We found that YouTube was the information source most linked to by users. The most retweeted post belonged to a verified Twitter user, indicating that the user may have had more influence on the platform. There was a small number of automated accounts (bots) and deleted accounts within the network. CONCLUSIONS Hashtags using and sharing conspiracy theories can be targeted in an effort to delegitimize content containing misinformation. Social media organizations need to bolster their efforts to label or remove content that contains misinformation. Public health authorities could enlist the assistance of influencers in spreading antinarrative content.


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