ICAR Research Data Repository for Knowledge Management

N. Thakur, “A Large-Scale Dataset of Twitter Chatter about Online Learning during the Current COVID-19 Omicron Wave,” Journal of Data, vol. 7, no. 8, p. 109, Aug. 2022, doi: 10.3390/data7080109

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, centered around information seeking and sharing, 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 files contain the raw version that comprises 52,868 Tweet IDs (that correspond to the same number of Tweets) and the cleaned and preprocessed version that contains 46,208 unique Tweet IDs. The dataset is compliant with the privacy policy, developer agreement, and guidelines for content redistribution of Twitter and the FAIR principles (Findability, Accessibility, Interoperability, and Reusability) principles for scientific data management.

The dataset comprises 7 .txt files. The raw version of this dataset comprises 6 .txt files (TweetIDs_Corona Virus.txt, TweetIDs_Corona.txt, TweetIDs_Coronavirus.txt, TweetIDs_Covid.txt, TweetIDs_Omicron.txt, and TweetIDs_SARS CoV2.txt) that contain Tweet IDs grouped together based on certain synonyms or terms that were used to refer to online learning and the Omicron variant of COVID-19 in the respective tweets. The cleaned and preprocessed version of this dataset is provided in the .txt file - TweetIDs_Duplicates_Removed.txt.

The dataset contains only Tweet IDs in compliance with the terms and conditions mentioned in the privacy policy, developer agreement, and guidelines for content redistribution of Twitter. The Tweet IDs need to be hydrated to be used. For hydrating this dataset the Hydrator application (link to download the application: https://github.com/DocNow/hydrator/releases and link to a step-by-step tutorial: https://towardsdatascience.com/learn-how-to-easily-hydrate-tweets-a0f393ed340e#:~:text=Hydrating%20Tweetsr) may be used.

The list of all the synonyms or terms that were used for the dataset development is as follows:

COVID-19: Omicron, COVID, COVID19, coronavirus, coronaviruspandemic, COVID-19, corona, coronaoutbreak, omicron variant, SARS CoV-2, corona virus

online learning: online education, online learning, remote education, remote learning, e-learning, elearning, distance learning, distance education, virtual learning, virtual education, online teaching, remote teaching, virtual teaching, online class, online classes, remote class, remote classes, distance class, distance classes, virtual class, virtual classes, online course, online courses, remote course, remote courses, distance course, distance courses, virtual course, virtual courses, online school, virtual school, remote school, online college, online university, virtual college, virtual university, remote college, remote university, online lecture, virtual lecture, remote lecture, online lectures, virtual lectures, remote lectures

• TweetIDs_Corona Virus.txt – Contains 321 Tweet IDs correspond to tweets that comprise the keywords – "corona virus" and one or more keywords/terms that refer to online learning


• TweetIDs_Corona.txt – Contains 1819 Tweet IDs correspond to tweets that comprise the keyword – "corona" or "coronaoutbreak" and one or more keywords/terms that refer to online learning


• TweetIDs_Coronavirus.txt – Contains 1429 Tweet IDs correspond to tweets that comprise the keywords – "coronavirus" or "coronaviruspandemic" and one or more keywords/terms that refer to online learning


• TweetIDs_Covid.txt – Contains 41088 Tweet IDs correspond to tweets that comprise the keywords – "COVID" or "COVID19" or "COVID-19" and one or more keywords/terms that refer to online learning


• TweetIDs_Omicron.txt – Contains 8198 Tweet IDs correspond to tweets that comprise the keywords – "omicron" or "omicron variant" and one or more keywords/terms that refer to online learning


• TweetIDs_SARS CoV2.txt – Contains 13 Tweet IDs correspond to tweets that comprise the keyword – "SARS-CoV-2" and one or more keywords/terms that refer to online learning


• TweetIDs_Duplicates_Removed.txt - A collection of 46208 unique Tweet IDs from all the 6 .txt files mentioned above after data preprocessing, data clearing, and removal of duplicate tweets