COVID-19 Misinformation on Social Media and Public’s Health Behavior: Understanding the Moderating Role of Situational Motivation and Credibility Evaluations

Barua, Zapan

doi:10.1007/s42087-022-00291-w

Cited by 5 publications

(3 citation statements)

References 56 publications

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“…Fourth, hedonic motivation is another influential factor for customer retention. The vi sual appeal of the website, pretty presentation of the food products in images, text, and video, gamification in the FDAs, hyper-link for broad information, celebrity endorsement of products, live product presentation through social media, and more can ensure the hedonic motivation of customer for continuous use of FDAs (Barua, 2022). Fifth, app developers may create long-term customer relationships by guiding healthy eating habits.…”

Section: C) Practical Implicationsmentioning

confidence: 99%

Consumers’ Food Delivery Apps (FDAs) Continuance Intention: An Empirical Investigation using the Extended UTAUT2 Model

Alauddin,

Akther

2023

GJMBR

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Online food delivery applications (FDAs), a novel alternative marketing channel, have been extensively adopted by both enterprises and customers in the restaurant sector. Despite the changing consumer attitude towards FDA services, there is still a dearth of research on understanding consumers’ continued intention to use FDA services in Bangladesh’s expanding food delivery market, particularly after the COVID-19 pandemic. To attain this goal, this study employed the widely used Extended Unified Theory of Acceptance and Use of Technology (UTAUT2). The model was tested was evaluated using partial least square structural equation modeling (PLS-SEM) on 350 respondents. According to the findings of the study, performance expectancy, social influence, facilitating conditions, hedonic motivation, price value, information quality, and convenience are all critical factors in maintaining the desire to utilize FDA services in Bangladesh. However, effort expectancy, habit, and time-saving were insignificant in the context of Bangladesh. This study contributes theoretically and practically to academics and practitioners working in areas related to online FDAs services.

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Section: C) Practical Implicationsmentioning

confidence: 99%

Consumers’ Food Delivery Apps (FDAs) Continuance Intention: An Empirical Investigation using the Extended UTAUT2 Model

Alauddin,

Akther

2023

GJMBR

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“…Also, vaccine hesitancy in Jordan and Kuwait was shown to be significantly impacted by social media rumors [5]. Furthermore, individuals tend to believe in conspiracy and religious misinformation, which makes them avoid proposed behavioral guidelines [6]. Therefore, social media disinformation is powerful in reducing vaccination coverage over time [7] while raising public health concerns regarding the impact of anti-vaccination content on platforms that increase vaccine hesitancy [8].…”

Section: Introductionmentioning

confidence: 99%

Facebook Post Credibility as a Predictor of Vaccine Hesitancy in the US

Aleksandric,

Dangal,

Nilizadeh

et al. 2024

Studies in Health Technology and Informatics

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Vaccine hesitancy represents a barrier to public health efforts aiming to mitigate the pandemic by performing global interventions. One of the reasons behind vaccine hesitancy is mistrust towards the health system that partially originated due to the misinformation shared over the internet. This study examined the association between the credibility of the sources regarding the COVID-19 vaccine posted on social media and the vaccination rate at the state level in the United States. Study findings suggest that sharing more Facebook posts with links to low-credibility sources about vaccination is associated with a lower number of new vaccinations at the state level in the US. This indicates an urgent need for social media-leveraged interventions through which public health officials can share reliable information to educate populations about vaccine benefits and reduce vaccine hesitancy.

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“…Various misinformation about the COVID-19 vaccine has been circulating on social media. For example, misinformation through conspiracy, such as "coronavirus vaccine destroys female fertility and makes men impotent" can lead people to refuse vaccination [13]. We set out to understand what topics and concepts related to disinformation appear in Twitter discourse on the impact of coronavirus on the reproductive health of men and women.…”

Section: Introductionmentioning

confidence: 99%

Methodology for identifying and tracking social media misinformation in tweets about the impact of the COVID-19 pandemic on reproductive health

Золотарев,

Хакимова,

Агравал

et al. 2023

Vestnik of Russian New University. Series «Complex Systems: Models, Analysis, Management»

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Цель исследования заключалась в разработке методики выявления и отслеживания дезинформации в социальных сетях, в частности в Твиттере, о влиянии коронавируса и COVID-вакцины на репродуктивное здоровье, одной из причин чего является недостаточная информированность об аспектах коронавирусной инфекции. Мы используем сочетание машинных и экспертных методов, последние научные статьи как эталон выявления дезинформации. Предлагаемая методика включает в себя изучение научных статей как источника достоверной правдивой информации по теме (стандарт информации) и сообщений в Твиттере (оценка соответствия информации стандарту). Результатом исследования является методика выявления дезинформации в сообщениях пользователей социальной сети. На основе этой методологии разработаны следующие аспекты проблемы: 1) формирование научного стандарта; 2) принцип сопоставления направлений научных исследований и дискуссий в Твиттере; 3) принцип контекстуального сопоставления пользовательского и научного представлений о проблемах. В отличие от существующих работ, сформулированы принципы, основанные на обработке информации из содержания научных статей и сообщений в социальных сетях. The purpose of the study was to develop a methodology for identifying and tracking social media misinformation in tweets about the impact of the coronavirus and COVID-vaccine on reproductive health, one of the reasons for which is the lack of awareness about aspects of the coronavirus infection. We use a combination of machine and expert methods, the latest scientific articles as the standard for detecting disinformation. The proposed methodology includes the study of scientific articles as a source of reliable truthful information about the topic (information standard) and Twitter messages (assessment of information compliance with the standard). The result of the study is the methodology for detecting disinformation in the messages of social network users. Based on this methodology, the following aspects of the problem have been developed: 1) the formation of a scientific standard; 2) the principle of comparing the directions of scientific research and discussions on Twitter; 3) the principle of contextual comparison of user and scientific ideas about problems. In contrast to the existing works, the principles based on the information from the content of scientific articles and messages from social networks processing are formulated.

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COVID-19 Misinformation on Social Media and Public’s Health Behavior: Understanding the Moderating Role of Situational Motivation and Credibility Evaluations

Cited by 5 publications

References 56 publications

Consumers’ Food Delivery Apps (FDAs) Continuance Intention: An Empirical Investigation using the Extended UTAUT2 Model

Consumers’ Food Delivery Apps (FDAs) Continuance Intention: An Empirical Investigation using the Extended UTAUT2 Model

Facebook Post Credibility as a Predictor of Vaccine Hesitancy in the US

Methodology for identifying and tracking social media misinformation in tweets about the impact of the COVID-19 pandemic on reproductive health

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