Conventional preventive measures during pandemic include social distancing and lockdown. Such measures in the time of social media brought about a new set of challenges - vulnerability to the toxic impact of online misinformation is high. A case in point is the prevailing COVID-19; as the virus propagates, so does the associated misinformation and fake news about it leading to infodemic. Since the outbreak, there has been a surge of studies investigating various aspects of the pandemic. Of interest to this chapter include studies centring on datasets from online social media platforms where the bulk of the public discourse happen. Consequently, the main goal is to support the fight against negative infodemic by (1) contributing a diverse set of curated relevant datasets (2) recommending relevant areas to study using the datasets (3) discussion on how relevant datasets, strategies and state-of-the-art IT tools can be leveraged in managing the pandemic.
|Title of host publication||Data Science Advancements in Pandemic and Outbreak Management|
|Editors||Eleana Asimakopoulou, Nik Bessis|
|Number of pages||19|
|ISBN (Print)||9781799867364, 1799867366, 9781799867371|
|Publication status||Published - 1 Apr 2021|
|Name||Advances in Data Mining and Database Management|
|Publisher||IGI Global |