Fabienne Lind, Maria Gruber and Hajo Boomgaarden received the Communication Methods and Measures Article of the Year Award of 2017! Congratulations!

Their paper argues that crowdsourcing platforms are commonly used for research in the humanities, social sciences and informatics, including the use of crowdworkers to annotate textual material or visuals. Utilizing two empirical studies, their article systematically assesses the potential of crowdcoding for less manifest contents of news texts, focusing on political actor evaluations. Specifically, Study 1 compares the reliability and validity of crowdcoded data to that of manual content analyses; Study 2 proceeds to investigate the effects of material presentation, different types of coding instructions and answer option formats on data quality. They find that the performance of the crowd recommends crowdcoded data as a reliable and valid alternative to manually coded data, also for less manifest contents. While scale manipulations affected the results, minor modifications of the coding instructions or material presentation did not significantly influence data quality. In sum, they find that crowdcoding appears a robust instrument to collect quantitative content data.

Fabienne Lind, Maria Gruber and Hajo G. Boomgaarden (2017) Content Analysis by the Crowd: Assessing the Usability of Crowdsourcing for Coding Latent Constructs. doi.org/10.1080/19312458.2017.1317338

Find the full paper here: doi.org/10.1080/19312458.2017.1317338