Crowdsourcing for quantifying transcripts: An exploratory study. (February 2016)

• Record Type: Journal Article
• Authors: Azzam, Tarek; Harman, Elena
• Is Part Of: Evaluation and program planning. Volume 54(2016:Feb.)
• Page Start: 63
• Page End: 73
• Publication Date: 2016-02
• Subjects: Crowdsourcing -- Qualitative analysis -- Stability -- Transcript coding -- Transcript rating -- Mechanical Turk -- MTurk; Health planning -- Periodicals; Medical care -- Evaluation -- Periodicals; 362.1068
• DOI: 10.1016/j.evalprogplan.2015.09.002
• Languages: English
• ISSNs: 0149-7189

Abstract

Highlights: Crowdsourcing is defined as the harnessing of the abilities of many people to complete a specific task or a set of tasks. In this study multiple samples of crowdsourced samples were asked to rate and code two different transcripts. The findings suggest that crowdsourced samples produced nearly identical ratings of the transcripts, and were able to consistently select the same supporting text from the transcripts. The findings indicate that crowdsourcing can potentially be used as an additional qualitative data analysis tool. Abstract: This exploratory study attempts to demonstrate the potential utility of crowdsourcing as a supplemental technique for quantifying transcribed interviews. Crowdsourcing is the harnessing of the abilities of many people to complete a specific task or a set of tasks. In this study multiple samples of crowdsourced individuals were asked to rate and select supporting quotes from two different transcripts. The findings indicate that the different crowdsourced samples produced nearly identical ratings of the transcripts, and were able to consistently select the same supporting text from the transcripts. These findings suggest that crowdsourcing, with further development, can potentially be used as a mixed method tool to offer a supplemental perspective on transcribed interviews.