Data Descriptor
Version 1
Preserved in Portico This version is not peer-reviewed
A Large-Scale Dataset of Twitter Chatter about Online Learning during the Current COVID-19 Omicron Wave
Version 1
: Received: 9 June 2022 / Approved: 10 June 2022 / Online: 10 June 2022 (03:42:25 CEST)
Version 2 : Received: 20 July 2022 / Approved: 21 July 2022 / Online: 21 July 2022 (08:05:19 CEST)
Version 2 : Received: 20 July 2022 / Approved: 21 July 2022 / Online: 21 July 2022 (08:05:19 CEST)
A peer-reviewed article of this Preprint also exists.
Thakur, N. A Large-Scale Dataset of Twitter Chatter about Online Learning during the Current COVID-19 Omicron Wave. Data 2022, 7, 109. Thakur, N. A Large-Scale Dataset of Twitter Chatter about Online Learning during the Current COVID-19 Omicron Wave. Data 2022, 7, 109.
Abstract
The COVID-19 Omicron variant, reported to be the most immune evasive variant of COVID-19, is resulting in a surge of COVID-19 cases globally. This has caused schools, colleges, and universities in different parts of the world to transition to online learning. As a result, social media platforms such as Twitter are seeing an increase in conversations related to online learning. Mining such conversations, such as Tweets, to develop a dataset can serve as a data resource for interdisciplinary research related to the analysis of interest, views, opinions, perspectives, attitudes, and feedback towards online learning during the current surge of COVID-19 cases caused by the Omicron variant. Therefore this work presents a large-scale public Twitter dataset of conversations about online learning since the first detected case of the COVID-19 Omicron variant in November 2021. The dataset is compliant with the privacy policy, developer agreement, and guidelines for content redistribution of Twitter, as well as with the FAIR principles (Findability, Accessibility, Interoperability, and Reusability) principles for scientific data management. The paper also briefly outlines some potential applications in the fields of Big Data, Data Mining, Natural Language Processing, and their related disciplines, with a specific focus on online learning during this Omicron wave that may be studied, explored, and investigated by using this dataset.
Keywords
COVID-19; COVID; Omicron; online learning; remote learning; online education; Twitter; dataset; Tweets; social media; Big Data
Subject
Computer Science and Mathematics, Information Systems
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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