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Infodemiology Framework for COVID-19 and Future Pandemics Using Artificial Intelligence to Address Misinformation and Disinformation

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Advances in Visual Informatics (IVIC 2021)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 13051))

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Abstract

The global fatality caused by the deadly COVID-19 already took 4.5 million lives and is still rapidly increasing. At the same time, Malaysian citizens have been inundated with the overabundance of news and information about COVID-19 since it hit the world in December 2019. Recent study by ISIS Malaysia discovered that WhatsApp and Facebook are the most used social media for misinformation at 39% and 34%, respectively. This phenomenon is termed as an infodemic which occurs when there is an excessive amount of information with undetermined level of accuracy. Hence, this situation makes it difficult for people to find reliable and truthful sources of information when they require it. Infodemiology is the scientific term used to describe the massive spread of information in a digital format particularly on the Internet which aims to guide the stakeholders such as the government on public health policy. Artificial Intelligence (AI) techniques hold potential solutions to address infodemic issue. This paper conceptualizes an Infodemiology Framework for COVID-19 and future pandemics towards addressing the proliferation of misinformation and disinformation on the Internet. Leveraging on AI techniques such as classification via clustering and decision tree algorithms, the research works will be conducted in five phases beginning with dataset collection phase, model building and algorithm selection phase, model refinement phase, model verification phase, and the model deployment phase. The proposed infodemiology framework has the potential to be integrated into the nation’s healthcare data warehousing system, the Malaysian Health Data Warehouse (MyHDW).

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Acknowledgements

The authors would like to thank Universiti Kebangsaan Malaysia under GP-2019-K021538 for sponsoring this publication.

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Authors and Affiliations

  1. Institute of IR4.0, Universiti Kebangsaan Malaysia, 43600 UKM, Bangi, Selangor, Malaysia

    Mohamad Taha Ijab & Mohamad Syahmi Shahril

  2. Faculty of Computer Science and Information Technology, Universiti Malaya, 50603, Kuala Lumpur, Malaysia

    Suraya Hamid

Authors
  1. Mohamad Taha Ijab
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  2. Mohamad Syahmi Shahril
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  3. Suraya Hamid
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Correspondence to Mohamad Taha Ijab .

Editor information

Editors and Affiliations

  1. Universiti Tenaga Nasional, Selangor, Malaysia

    Halimah Badioze Zaman

  2. Dublin City University, Dublin, Ireland

    Alan F. Smeaton

  3. National Central University, Jhongli, Taiwan

    Timothy K. Shih

  4. Queen Mary University of London, London, UK

    Sergio Velastin

  5. Toyo University, Tokyo, Japan

    Tada Terutoshi

  6. University of Southern Denmark, Odense, Denmark

    Bo Nørregaard Jørgensen

  7. Universiti Tenaga Nasional, Selangor, Malaysia

    Hazleen Aris

  8. Universiti Tenaga Nasional, Selangor, Malaysia

    Nazrita Ibrahim

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Ijab, M.T., Shahril, M.S., Hamid, S. (2021). Infodemiology Framework for COVID-19 and Future Pandemics Using Artificial Intelligence to Address Misinformation and Disinformation. In: Badioze Zaman, H., et al. Advances in Visual Informatics. IVIC 2021. Lecture Notes in Computer Science(), vol 13051. Springer, Cham. https://doi.org/10.1007/978-3-030-90235-3_46

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  • DOI: https://doi.org/10.1007/978-3-030-90235-3_46

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