Crowdsourcing for quantifying transcripts: An exploratory study |
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| Affiliation: | 1. European Centre for Living Technology, Ca’ Foscari University of Venice, S. Marco 2940, 30124 Venice, Italy;2. Department of Innovation and Economic Organization, BI Norwegian Business School, Nydalsveien 37, N-0442 Oslo, Norway;1. Faculty of Economics and Management, National University of Malaysia, UKM Bangi, 43600 Selangor, Malaysia;2. Department of Strategic Management and Globalization, Copenhagen Business School, Kilevej 14, 2000 Frederiksberg, Denmark;3. Syntek Corporation, 4.669 Evaluation and Planning, 2279 Mershon Drive, Ann Arbor, 48103 MI, United States;1. University of Malaya, Faculty of Science, Department of Science & Technology Studies, 50603 Kuala Lumpur, Malaysia;2. University of Malaya, Centre for Civilisational Dialogue, 50603 Kuala Lumpur, Malaysia;1. Department of Educational Research, Lancaster University, Bailrigg, Lancaster LA1 4YW, United Kingdom;2. Family and Community Social Services Program, University of Guelph-Humber, 207 Humber College Blvd., Toronto, ON, M9W 5L7, Canada;1. University of North Carolina at Chapel Hill, UNC Eshelman School of Pharmacy, Division of Pharmaceutical Outcomes and Policy, Asheville, NC 28804, United States;2. Georgia Southern University, Jiann-Ping Hsu College of Public Health, Department of Community Health Behavior & Education, Statesboro, GA 30460, United States;3. University of South Florida, Department of Educational Measurement and Research, Tampa, FL 33620, United States |
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| 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. |
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| Keywords: | Crowdsourcing Qualitative analysis Stability Transcript coding Transcript rating Mechanical Turk MTurk |
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