Challenges in Combating COVID-19 Infodemic -- Data, Tools, and Ethics

Ding, Kaize; Shu, Kai; Li, Yichuan; Bhattacharjee, Amrita; Liu, Huan

doi:10.48550/arxiv.2005.13691

Cited by 6 publications

(5 citation statements)

References 7 publications

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“…Machine learning techniques have also been adapted to detect misinformation. The work in [35] discussed the challenges in designing and developing an AI solutions for infodemic detection. Moreover, authors presented a tool to estimate whether an article is a misinformation based on URL checker, fake news classifier, and website matcher.…”

Section: Related Workmentioning

confidence: 99%

Eating Garlic Prevents COVID-19 Infection: Detecting Misinformation on the Arabic Content of Twitter

Alqurashi¹,

Hamoui²,

Alashaikh³

et al. 2021

Preprint

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The rapid growth of social media content during the current pandemic provides useful tools for disseminating information which has also become a root for misinformation. Therefore, there is an urgent need for fact-checking and effective techniques for detecting misinformation in social media. In this work, we study the misinformation in the Arabic content of Twitter. We construct a large Arabic dataset related to COVID-19 misinformation and gold-annotate the tweets into two categories: misinformation or not. Then, we apply eight different traditional and deep machine learning models, with different features including word embeddings and word frequency. The word embedding models (FASTTEXT and word2vec) exploit more than two million Arabic tweets related to COVID-19. Experiments show that optimizing the area under the curve (AUC) improves the models' performance and the Extreme Gradient Boosting (XGBoost) presents the highest accuracy in detecting COVID-19 misinformation online.

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Section: Related Workmentioning

confidence: 99%

Eating Garlic Prevents COVID-19 Infection: Detecting Misinformation on the Arabic Content of Twitter

Alqurashi¹,

Hamoui²,

Alashaikh³

et al. 2021

Preprint

View full text Add to dashboard Cite

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“…3 Logistic Regression: a statistical technique that aims to produce a model that allows the prediction of values taken by a categorical variable. 4 Naive Bayes: family of simple "probabilistic classifiers" based on the application of the Bayes' theorem. 5 API : set of routines and programming patterns for accessing Twitter's own software or web-based platform.…”

Section: Pythonmentioning

confidence: 99%

“…Most of this work is related to contenders promoted on the Kaggle platform 1 . Some authors like [4] and [2] use the term infodemic to describe this phenomenon of fake news about the coronavirus. Some social networks, like Twitter and Facebook, have released tools to combat fake news.…”

Section: Introductionmentioning

confidence: 99%

The use of Data Augmentation as a technique for improving neural network accuracy in detecting fake news about COVID-19

Júnior¹,

Cruz²,

Wyzykowski³

et al. 2022

Preprint

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This paper aims to present how the application of Natural Language Processing (NLP) and data augmentation techniques can improve the performance of a neural network for better detection of fake news in the Portuguese language. Fake news is one of the main controversies during the growth of the internet in the last decade. Verifying what is fact and what is false has proven to be a difficult task, while the dissemination of false news is much faster, which leads to the need for the creation of tools that, automated, assist in the process of verification of what is fact and what is false. In order to bring a solution, an experiment was developed with neural network using news, real and fake, which were never seen by artificial intelligence (AI). There was a significant performance in the news classification after the application of the mentioned techniques.Keywords Fake News • COVID-19 • AI • Data Augmentation • NLP 1 Kaggle: an online community of data scientists and machine learning professionals subsidiary of Google.

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“…The study by (Pulido et al 2020) analyzed 1,000 tweets and categorized them based on factuality: (i) False information, (ii) Sciencebased evidence, (iii) Fact-checking tweets, (iv) Mixed information, (v) Facts, (vi) Facts, (vii) Other, and (viii) Not valid. Finally, Ding et al (2020) have a position paper discussing the challenges in combating the COVID-19 infodemic in terms of data, tools, and ethics. See also a recent survey by Shuja et al (2020).…”

Section: Related Workmentioning

confidence: 99%

Fighting the COVID-19 Infodemic in Social Media: A Holistic Perspective and a Call to Arms

Alam

Dalvi

Shaar

et al. 2021

ICWSM

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With the outbreak of the COVID-19 pandemic, people turned to social media to read and to share timely information including statistics, warnings, advice, and inspirational stories. Unfortunately, alongside all this useful information, there was also a new blending of medical and political misinformation and disinformation, which gave rise to the first global infodemic. While fighting this infodemic is typically thought of in terms of factuality, the problem is much broader as malicious content includes not only fake news, rumors, and conspiracy theories, but also promotion of fake cures, panic, racism, xenophobia, and mistrust in the authorities, among others. This is a complex problem that needs a holistic approach combining the perspectives of journalists, fact-checkers, policymakers, government entities, social media platforms, and society as a whole. With this in mind, we define an annotation schema and detailed annotation instructions that reflect these perspectives. We further deploy a multilingual annotation platform, and we issue a call to arms to the research community and beyond to join the fight by supporting our crowdsourcing annotation efforts. We perform initial annotations using the annotation schema, and our initial experiments demonstrated sizable improvements over the baselines.

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Challenges in Combating COVID-19 Infodemic -- Data, Tools, and Ethics

Cited by 6 publications

References 7 publications

Eating Garlic Prevents COVID-19 Infection: Detecting Misinformation on the Arabic Content of Twitter

Eating Garlic Prevents COVID-19 Infection: Detecting Misinformation on the Arabic Content of Twitter

The use of Data Augmentation as a technique for improving neural network accuracy in detecting fake news about COVID-19

Fighting the COVID-19 Infodemic in Social Media: A Holistic Perspective and a Call to Arms

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