图书简介

Chapter 1: Introduction \\ A Scientific Revolution in the Making \\ A Brief History of Online Research in the Social and Behavioral Sciences: From HTML 2.0 to Mechanical Turk \\ The Use of Online Samples in Applied Behavioral Research \\ Amazon Mechanical Turk \\ Chapter 2: The Mechanical Turk EcosystemLeib Litman, Cheskie Rosenzweig, Jonathan Robinson \\ How Quality is Maintained \\ Reputation Mechanism \\ Selectively Recruiting Specific Workers \\ Protections for Workers \\ Communicating with Workers \\ A Worker’s Perspective \\ Worker Communities \\ Chapter 3: Conducting a Study on Mechanical Turk \\ Sample Project \\ Setting up a Requester Account on Mechanical Turk \\ Creating a HIT \\ The ‘Design Layout’ tab \\ Monitoring Progress on the Requester’s Dashboard \\ When a Worker Runs Out of Time \\ Sample Study Results \\ Conducting Follow-up Studies Using Requester-Issued Qualifications \\ Appendix A: Checklist for best practices of setting up a Mechanical Turk HIT \\ Chapter 4: API and Third Party Apps \\ Third Party API-based Platforms \\ Common Uses for API Scripts and Third Party API-based Apps \\ TurkPrime \\ Chapter 5: Data Quality Issues on MTurkJesse Chandler, Gabriele Paolacci, David Hauser \\ Defining and Measuring Data Quality \\ Measuring Individual Participant Data Quality \\ Causes of and Cures for Poor Data Quality \\ Concluding Thoughts \\ Chapter 6: Who are the Mechanical Turk Workers? \\ Sources of Data \\ Location of Workers in the US \\ Demographics of Mechanical Turk \\ Chapter 7: Sampling Mechanical Turk Workers: Problems and Solutions \\ Sampling on Mechanical Turk \\ Sources of Sampling Bias \\ The Problem of Superworkers \\ Time-of-day Effects \\ Pay Rate \\ Dropout \\ Sampling Best Practices \\ Chapter 8: Data Representativeness of Mechanical Turk Samples \\ Representativeness, surveys, and survey sampling \\ The methodology of survey sampling \\ Mechanical Turk as a sampling frame \\ The fit-for-purpose framework \\ Chapter Overview: \\ Chapter 9: Conducting Longitudinal Research on Amazon Mechanical Turk \\ Why Longitudinal Research? \\ Retention, Longitudinal Research, and MTurk \\ Case Studies \\ Best practices for longitudinal research \\ Chapter 10: Beyond Mechanical Turk: Using Online Market Research Platforms \\ Limitations of MTurk \\ Online probability-based panels \\ Online market research platforms \\ Overall comparisons between Mechanical Turk and market research platforms \\ Chapter 11: Conducting Ethical Online Research: A Data-Driven Approach \\ Historical background \\ Risk of harm in online research \\ Research on sensitive topics \\ A deeper dive into controversial and complex issues \\ Economics of Mechanical Turk: Considerations for setting wages \\ Setting wages: Considerations of ethics and methodology \\ Considerations for rejecting, blocking and disqualifying workers. \\ Practical advice for requester/worker interactions \\ Anonymity \\ Appendix A

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