What is it about?
Big data powers everything from chatbots and sports analytics to medical research, but its massive quantity and mixed quality make it easy to draw the wrong conclusions without time-consuming and expensive checking of data and results by humans. This paper demonstrates, with 3 real-world applications, how crowdsourcing tools like Amazon Mechanical Turk can be used to augment big data and improve its value.
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Why is it important?
Big data undergirds more critical decisions every day, many of which connect to complex social issues. We define evidence-based best practices for improving its value and accuracy with less cost and effort, focusing on recommendations that anyone can implement to maximize the impact of the augmentation and the data itself.
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This page is a summary of: Enhancing big data in the social sciences with crowdsourcing: Data augmentation practices, techniques, and opportunities, PLoS ONE, June 2020, PLOS,
DOI: 10.1371/journal.pone.0233154.
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