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Part 1: Document Description
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Citation |
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Title: |
Replication Data for: Optimising Self-Organised Volunteer Efforts in Response to the COVID-19 Pandemic |
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Identification Number: |
doi:10.7910/DVN/YUOOBB |
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Distributor: |
Harvard Dataverse |
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Date of Distribution: |
2022-04-20 |
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Version: |
1 |
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Bibliographic Citation: |
Zhang, Anping; Zhang, Ke; Li, Wanda; Wang, Yue; Li, Yang; Zhang, Lin, 2022, "Replication Data for: Optimising Self-Organised Volunteer Efforts in Response to the COVID-19 Pandemic", https://doi.org/10.7910/DVN/YUOOBB, Harvard Dataverse, V1 |
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Citation |
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Title: |
Replication Data for: Optimising Self-Organised Volunteer Efforts in Response to the COVID-19 Pandemic |
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Identification Number: |
doi:10.7910/DVN/YUOOBB |
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Authoring Entity: |
Zhang, Anping (Tsinghua-Berkeley Shenzhen Institute, Tsinghua University) |
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Zhang, Ke (Tsinghua-Berkeley Shenzhen Institute, Tsinghua University) |
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Li, Wanda (Tsinghua-Berkeley Shenzhen Institute, Tsinghua University) |
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Wang, Yue (Tsinghua University) |
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Li, Yang (Tsinghua-Berkeley Shenzhen Institute, Tsinghua University) |
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Zhang, Lin (Tsinghua-Berkeley Shenzhen Institute, Tsinghua University) |
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Distributor: |
Harvard Dataverse |
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Access Authority: |
Li, Yang |
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Depositor: |
Zhang, Anping |
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Date of Deposit: |
2022-03-11 |
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Holdings Information: |
https://doi.org/10.7910/DVN/YUOOBB |
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Study Scope |
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Keywords: |
Computer and Information Science, Engineering, Social Sciences, Computer and Information Science, Engineering, Social Sciences, COVID-19, Volunteer, Crowdsource, Coronavirus |
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Abstract: |
The attached file includes all data and code for the analysis. |
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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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Label: |
Data_and_code.tar |
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Notes: |
application/x-tar |