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Enhancing big data in the social sciences with crowdsourcing: Data augmentation practices, techniques, and
Nathaniel D Porter1, Ashton M Verdery2, S Michael Gaddis3
1Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America.
Plos One
|June 11, 2020
Summary
Online crowdsourcing can enhance big data reliability for social research. This method addresses concerns about data validity and research value, offering a scalable solution for data augmentation.
Area of Science:
- Social Sciences
- Data Science
- Information Science
Background:
- Big data is proposed to revolutionize social research, but faces skepticism regarding reliability and decontextualization.
- Much big data is not originally intended for social research purposes.
- Data augmentation is crucial for improving the validity and research value of big data.
Purpose of the Study:
- To explore online crowdsourcing as a method for data augmentation in social research.
- To assess the strengths and limitations of crowdsourcing for enhancing big data.
- To develop best practices and a reporting template for crowdsourced data augmentation.
Main Methods:
- Investigated three empirical cases using Amazon Mechanical Turk for data augmentation.
- Employed crowdsourcing to verify automated coding, link online databases, and gather data on online resources.
- Developed guidelines and a reporting template based on case study findings.
Main Results:
- Crowdsourcing demonstrated potential for verifying automated coding and linking disparate data sources.
- Gathering data on online resources via crowdsourcing proved feasible.
- The study identified specific strengths and limitations of using crowdsourcing for big data augmentation.
Conclusions:
- Carefully designed and implemented crowdsourcing can effectively augment big data for social research.
- Crowdsourcing helps address concerns about the reliability and decontextualization of big data.
- Rigorous documentation and adherence to best practices are essential for reproducible crowdsourced research.
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