Accurate, Fast, But Not Always Cheap: Evaluating 'Crowdcoding' as an Alternative Approach to Analyze Social Media Data
| Autor: | Mona Jalal, Margrit Betke, Sha Lai, Prakash Ishwar, Lei Guo, Kate K. Mays |
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| Rok vydání: | 2019 |
| Předmět: |
Multimedia
business.industry Computer science Communication 05 social sciences Sentiment analysis 050801 communication & media studies 16. Peace & justice Crowdsourcing computer.software_genre 0506 political science 0508 media and communications Content analysis 050602 political science & public administration Social media The Internet business computer Coding (social sciences) |
| Zdroj: | Journalism & Mass Communication Quarterly. 97:811-834 |
| ISSN: | 2161-430X 1077-6990 |
| Popis: | Crowdcoding, a method that outsources “coding” tasks to numerous people on the internet, has emerged as a popular approach for annotating texts and visuals. However, the performance of this approach for analyzing social media data in the context of journalism and mass communication research has not been systematically assessed. This study evaluated the validity and efficiency of crowdcoding based on the analysis of 4,000 tweets about the 2016 U.S. presidential election. The results show that compared with the traditional quantitative content analysis, crowdcoding yielded comparably valid results and was superior in efficiency, but was more expensive under most circumstances. |
| Databáze: | OpenAIRE |
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