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Content Analysis by the Crowd: Assessing the Usability of Crowdsourcing for Coding Latent Constructs
Fabienne Lind1, Maria Gruber1, Hajo G Boomgaarden1
1Department of Communications, University of Vienna, Vienna, Austria.
Communication Methods and Measures
|November 10, 2017
Summary
Crowdcoding offers a reliable and valid method for analyzing news texts, even for subtle political actor evaluations. This crowdsourcing approach provides a robust alternative to traditional manual content analysis for quantitative data collection.
Area of Science:
- Social Sciences
- Informatics
- Humanities
Background:
- Crowdsourcing is widely used in research for data annotation.
- Its application for analyzing less manifest content, like political evaluations in news, requires systematic assessment.
Purpose of the Study:
- To evaluate crowdcoding's reliability and validity for analyzing subtle news content.
- To investigate factors influencing data quality in crowdcoded political actor evaluations.
Main Methods:
- Two empirical studies were conducted.
- Study 1: Compared crowdcoded data with manual content analysis.
- Study 2: Examined effects of material presentation, instructions, and answer formats on data quality.
Main Results:
- Crowdcoded data demonstrated reliability and validity comparable to manual content analysis.
- Minor changes in coding instructions or presentation did not significantly impact data quality.
- Scale manipulations, however, did affect the results.
Conclusions:
- Crowdcoding is a robust and viable instrument for collecting quantitative content data, even for nuanced analyses.
- It serves as a reliable and valid alternative to manual coding methods.
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