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Social Media during COVID-19 & MonkeyPox 2023 : SPECIAL ISSUE: The Role of Social Media during the Ongoing Outbreaks of COVID-19 and Monkeypox: Applications, Use-Cases, Analytics, and Beyond


When N/A
Where N/A
Submission Deadline Mar 15, 2023
Categories    COVID-19   monkeypox   social media   twitter

Call For Papers

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This is a special issue of Information (ISSN 2078-2489). Information is an international, scientific open-access journal of information science and technology, data, knowledge, and communication, published monthly by MDPI.

Journal Rank: CiteScore - Q2 (Information Systems)

High Visibility: indexed within Scopus, ESCI (Web of Science), Ei Compendex, dblp, and other databases. For complete information about the indexing of this journal, please refer to:

Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 18.9 days after submission; acceptance to publication is undertaken in 3.4 days (median values for papers published in this journal in the first half of 2022).

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Dear Colleagues,

The ongoing outbreaks of COVID-19 and monkeypox (mpox) have resulted in people from all over the world using social media platforms for information seeking and sharing, as well as for the communication of views, opinions, feedback, perspectives, and suggestions on a wide range of topics related to these outbreaks, which include policies for reducing the spread of these viruses, treatments, vaccines, school closures, and travel guidelines, just to name a few.

Since the initial cases in December 2019, the SARS-CoV-2 virus has undergone multiple mutations, and as a result, several variants have been detected in different parts of the world. Some of these include Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), Epsilon (B.1.427 and B.1.429), Eta (B.1.525), Iota (B.1.526), Kappa (B.1.617.1), Zeta (P.2), Mu (B.1.621 and B.1.621.1), and Omicron (B.1.1.529, BA.1, BA.1.1, BA.2, BA.3, BA.4, and BA.5) [1]. At present, there have been more than 674,814,341 cases and 6,759,130 deaths on a global scale due to COVID-19 [2].

Monkeypox (mpox) is a re-emerging zoonotic disease. At present, 85,158 cases have been recorded, with 83,872 cases in locations that have not historically reported mpox [3].

These virus outbreaks have served as β€œcatalysts” for social media usage and are resulting in the generation of tremendous amounts of Big Data related to such paradigms of social media behavior. These Big Data can be used as a data resource for the investigation of different research questions, use cases, and applications to advance research and developments in these fields.

This Special Issue invites papers presenting new discoveries, theoretical findings, practical solutions, use cases, analytical findings, novel applications, and results based on studying, analyzing, and interpreting the Big Data on social media platforms generated in the context of the ongoing outbreaks of COVID-19 and monkeypox. Specific topics could include but are not limited to text mining, text classification, text clustering, text categorization, topic modeling, opinion mining, sentiment analysis, aspect-based sentiment analysis, spam detection, fake news tracking, misinformation detection, and identification of conspiracy theories on social media platforms, such as Twitter, Facebook, Instagram, YouTube, etc., with a central focus on COVID-19 or monkeypox (mpox).

Authors are invited to contribute their original and unpublished works. Both research and review papers are welcome. Research papers presenting preliminary and proof-of-concept results are also welcome. Authors may also submit extended versions of their conference papers. However, authors of such papers should make significant improvements/extensions to their conference papers, and the details of these improvements/extensions should be clearly outlined in the cover letter accompanying the paper submission.


[1] CDC, β€œSARS-CoV-2 variant classifications and definitions,” Centers for Disease Control and Prevention, 29-Aug-2022. Available: [Accessed: 29-Jan-2023].

[2] β€œCOVID live - Coronavirus statistics - worldometer,” Available: [Accessed: 29-Jan-2023].

[3] CDC, β€œ2022 mpox outbreak global map,” Centers for Disease Control and Prevention, 27-Jan-2023. Available: [Accessed: 29-Jan-2023].

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Dr. Nirmalya Thakur
Department of Computer Science, Emory University, Atlanta, GA 30322, USA
Interests: human–computer interaction; big data; artificial intelligence; machine learning; data science; Internet of Things; and natural language processing

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