ArticleTelematics and informatics2021
FibVID: Comprehensive fake news diffusion dataset during the COVID-19 period.
Article in Telematics and informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 53 citations in OpenAlex.
- Analysing health misinformation with advanced centrality metrics in online social networks.PLOS digital health · 2025Article
- Identifying Disinformation on the Extended Impacts of COVID-19: Methodological Investigation Using a Fuzzy Ranking Ensemble of Natural Language Processing Models.Journal of medical Internet research · 2025Article
- Article
- Social media users' perceptions about health mis- and disinformation on social media.Health affairs scholar · 2023Article
- Data-driven analytics of COVID-19 'infodemic'.International journal of data science and analytics · 2023Article
- CRNet: a multimodal deep convolutional neural network for customer revisit prediction.Journal of big data · 2023Article
- A comparative analysis of the COVID-19 Infodemic in English and Chinese: insights from social media textual data.Frontiers in public health · 2023Article
- Social media mining under the COVID-19 context: Progress, challenges, and opportunities.International journal of applied earth observation and geoinformation : ITC journal · 2022Article
- Infodemic and fake news - A comprehensive overview of its global magnitude during the COVID-19 pandemic in 2021: A scoping review.International journal of disaster risk reduction : IJDRR · 2022Article
- Utilizing deep learning models for ternary classification in COVID-19 infodemic detection.Digital healthArticle
- Health Misinformation Detection: Approaches, Challenges and Opportunities.Inquiry : a journal of medical care organization, provision and financingReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As the SARS-CoV-2 (COVID-19) pandemic has run rampant worldwide, the dissemination of misinformation has sown confusion on a global scale. Thus, understanding the propagation of fake news and implementing countermeasures has become exceedingly important to the well-being of society. To assist this cause, we produce a valuable dataset called FibVID (Fake news information-broadcasting dataset of COVID-19), which addresses COVID-19 and non-COVID news from three key angles. First, we provide truth and falsehood (T/F) indicators of news items, as labeled and validated by several fact-checking platforms (e.g., Snopes and Politifact). Second, we collect spurious-claim-related tweets and retweets from Twitter, one of the world's largest social networks. Third, we provide basic user information, including the terms and characteristics of "heavy fake news" user to present a better understanding of T/F claims in consideration of COVID-19. FibVID provides several significant contributions. It helps to uncover propagation patterns of news items and themes related to identifying their authenticity. It further helps catalog and identify the traits of users who engage in fake news diffusion. We also provide suggestions for future applications of FibVID with a few exploratory analyses to examine the effectiveness of the approaches used.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.