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Part 1: Document Description
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Citation |
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Title: |
Replication Data for: Misleading the Covid-19 vaccination discourse on Twitter: An exploratory study of infodemic around the pandemic |
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Identification Number: |
doi:10.21979/N9/QMLIJQ |
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Distributor: |
DR-NTU (Data) |
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Date of Distribution: |
2022-05-11 |
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Version: |
1 |
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Bibliographic Citation: |
Sharma, Shakshi; Sharma, Rajesh; Datta, Anwitaman, 2022, "Replication Data for: Misleading the Covid-19 vaccination discourse on Twitter: An exploratory study of infodemic around the pandemic", https://doi.org/10.21979/N9/QMLIJQ, DR-NTU (Data), V1 |
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Citation |
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Title: |
Replication Data for: Misleading the Covid-19 vaccination discourse on Twitter: An exploratory study of infodemic around the pandemic |
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Identification Number: |
doi:10.21979/N9/QMLIJQ |
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Authoring Entity: |
Sharma, Shakshi (University of Tartu, Estonia) |
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Sharma, Rajesh (University of Tartu, Estonia) |
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Datta, Anwitaman (Nanyang Technological University) |
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Software used in Production: |
any software that can handle text files |
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Distributor: |
DR-NTU (Data) |
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Access Authority: |
Datta, Anwitaman |
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Depositor: |
Datta, Anwitaman |
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Date of Deposit: |
2022-05-11 |
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Holdings Information: |
https://doi.org/10.21979/N9/QMLIJQ |
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Study Scope |
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Keywords: |
Computer and Information Science, Computer and Information Science, Covid-19, Vaccination, Misinformation, Tweet |
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Abstract: |
Two files are provided. Each contain Tweet ID, Label pairs. Label 1 indicates misleading tweets, while label 0 is used otherwise. One file contains 1500 manually annotated entries, while the other contains 114,635 where the labels are predicted algorithmically (see accompanying publication, arXiv:2108.10735, for details). The manual annotation was best-effort, and the predicted labels are not vetted, and is limited by the quality of manual labels used to train the algorithms, as well as any other shortcomings of the algorithms. The data is being provided on an as-is basis, but we do not accept any responsibility for its use, nor any consequences therefrom. The data is provided following the FAIR Data Principles (Findable, Accessible, Interoperable, and Reusable) and Twitter's content redistribution policy (see: <a href="https://developer.twitter.com/en/developer-terms">https://developer.twitter.com/en/developer-terms</a>) |
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Kind of Data: |
coded textual |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Other Study Description Materials |
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Related Publications |
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Citation |
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Identification Number: |
2108.10735 |
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Bibliographic Citation: |
Sharma, S., Sharma, R., & Datta, A. (2021). Misleading the Covid-19 vaccination discourse on Twitter: An exploratory study of infodemic around the pandemic. arXiv preprint arXiv:2108.10735. |
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Label: |
Misleading_COVID19_manual_labels.txt |
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Notes: |
text/plain |
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Label: |
PredictedLabelsMisleading_COVID19_vaccine_tweets.txt |
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Notes: |
text/plain |