Leveraging Social Media Data for COVID-19 Studies

• URL: http://arxiv.org/abs/2606.10459v1
• Date: Tue, 09 Jun 2026 06:14:36 GMT
• Title: Leveraging Social Media Data for COVID-19 Studies
• Abstract summary: Social media has been one of the most used platforms to get the latest news and information related to COVID 19.<n>This chapter describes linguistic, visual, and emotional indicators expressed in user disclosures.<n>This chapter also categorizes social media data used, introduces different deployed machine learning, feature engineering, natural language processing, and survey methods.
• Score: 0.0
• License: http://creativecommons.org/publicdomain/zero/1.0/
• Abstract: Nowadays, social media networks have become widely preferred sources of information. Especially during the time of the Coronavirus disease 2019 COVID 19 pandemic, social media has been one of the most used platforms to get the latest news and information related to COVID 19. Social media are popular because they offer free access to their registered users and allow them to do posting, disseminate information, and respond to others postings. With almost 4.6 billion social media users worldwide, it is not surprising the significant amount of information shared through these platforms could affect how people perceive and cope with the pandemic that we are facing right now. With decent use, social media can be a beneficial digital tool to spread reliable news and public awareness for patients, clinicians, and society. Specifically, this chapter describes linguistic, visual, and emotional indicators expressed in user disclosures. Thus, in this chapter, the related studies of social media platforms usage during the COVID 19 pandemic are explored and discussed in detail. This chapter also categorizes social media data used, introduces different deployed machine learning, feature engineering, natural language processing, and survey methods, and outlines directions for future research.

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