Predictors and outcomes of individual knowledge on early-stage pandemic: Social media, information credibility, public opinion, and behaviour in a large-scale global study

Chawla, Yash; Radziwon, Agnieszka; Scaringella, Laurent; Carlson, Ewa Lazarczyk; Greco, Marco; Silveira, Paulo Duarte; Aguiar, Eduardo Pestana de; Shen, Qingyang; Will, Markus; Kowalska-Pyzalska, Anna

doi:10.1016/j.ipm.2021.102720

Cited by 12 publications

(2 citation statements)

References 42 publications

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“…The authors commissioned diverse means to distribute the survey, including mailing lists at their universities, social media platforms such as Facebook, LinkedIn, Instagram, and Twitter, and private messages. Per Baltar and Brunet's [86] recommendation, also employed by Chawla et al [87], participants were urged to share the questionnaire with their network after completing it, aiming to boost the number of responses and enhance the study's external validity.…”

Section: Samplingmentioning

confidence: 99%

Gen Z’s Attitude towards Green Image Destinations, Green Tourism and Behavioural Intention Regarding Green Holiday Destination Choice: A Study in Poland and India

2023

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Using PLS-SEM, this article proposes and verifies a model among Gen Z that captures the relationship between attitudes towards the environmental ecosystem and green tourism, personal and social norms regarding pro-environmental behaviour, perceived behavioural control, perceived green image of destinations (PGID), behavioural intentions regarding green holiday destinations (GHD), and willingness to pay (WTP) more for visiting them. The paper also verifies whether intercultural differences exist in the relationships between these variables. The most important results indicate that (1) for Gen Z, the perceived green image of destinations has the strongest impact on intention to travel to green holiday destinations; (2) the proposed variables explain the willingness to visit green holiday destinations to a much greater extent than the WTP a higher price for such trips. This study contributes to the literature concerning generational changes in tourism, pro-environmental (transition) planning, and the growing green economy and marketing.

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Section: Samplingmentioning

confidence: 99%

Gen Z’s Attitude towards Green Image Destinations, Green Tourism and Behavioural Intention Regarding Green Holiday Destination Choice: A Study in Poland and India

2023

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“…Scientific knowledge level theory and an external online rumor control technique were used in the model. Several researchers have experimented with several techniques to detect fake news and rumors about Covid-19 and non-medical concerns transmitted through social media (Ahmed et al, 2021;Burel et al, 2021;Chawla et al, 2021;Kumari et al, 2021;Ling, 2021;Przybyła & Soto, 2021;Samadi et al, 2021;Wang et al, 2021;Yao et al, 2021;Zhou, Li, et al, 2021;Zhou, Xiu, et al, 2021). Since it is not the scope of the paper, we have just given the references.…”

Section: Related Workmentioning

confidence: 99%

Ta-Whi

Bagla

Kumar

2023

International Journal of Software Science and Computational Intelligence

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The healthcare data available on social media has exploded in recent years. The cures and treatments suggested by non-medical experts can lead to more damage than expected. Assuring the credibility of the information conveyed is an enormous challenge. This study aims to categorize the credibility of online health information into multiple classes. This paper proposes a model named Text Analysis of Web-based Health Information (TA-WHI), based on an algorithm designed for this. It categorizes health-related social media feeds into five categories: sufficient, fabricated, meaningful, advertisement, and misleading. The authors have created their own labeled dataset for this model. For data cleaning, they have designed a dictionary having nouns, adverbs, adjectives, negative words, positive words, and medical terms named MeDF. Using polarity and conditional procedure, the data is ranked and classified into multiple classes. The authors evaluate the performance of the model using deep-learning classifiers such as CNN, LSTM, and CatBoost. The suggested model has attained an accuracy of 98% with CatBoost.

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From Screens to Shopping Carts: Unravelling the Impact of Digital Influencers’ Credibility on Hyper-Local Brand Perception and Purchase Intentions

Hoor,

Singh,

Vigneswara Ilavarasan

et al. 2023

IFIP Advances in Information and Communication Technology

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Predictors and outcomes of individual knowledge on early-stage pandemic: Social media, information credibility, public opinion, and behaviour in a large-scale global study

Cited by 12 publications

References 42 publications

Gen Z’s Attitude towards Green Image Destinations, Green Tourism and Behavioural Intention Regarding Green Holiday Destination Choice: A Study in Poland and India

Gen Z’s Attitude towards Green Image Destinations, Green Tourism and Behavioural Intention Regarding Green Holiday Destination Choice: A Study in Poland and India

Ta-Whi

From Screens to Shopping Carts: Unravelling the Impact of Digital Influencers’ Credibility on Hyper-Local Brand Perception and Purchase Intentions

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