[ecrea] ICA pre-con / Crowdsourcing as a Content Analysis Tool

ICA Preconference: Crowdsourcing as a Content Analysis Tool


May 24

Hilton Prague

Crowdsourcing is a popular method in computer science for categorizing 
and classifying text and objects. This preconference introduces 
crowdsourcing for communication researchers as an emerging content 
analysis method. Rather than rely on a few human coders to carry out a 
content analysis, the crowdsourcing approach outsources coding tasks to 
numerous people online (e.g., multiple people code the same item), and 
applies an aggregation policy to make a decision on a given item.

Through a hands-on workshop and research presentations, this 
preconference explores:

1) Different crowdsourcing platforms to carry out a project. A 
demonstration will be given to show how to use two different 
crowdsourcing platforms: Amazon’s Mechanical Turk (MTurk), a 
well-established service, and Crowdflower, an emerging service. In the 
hands-on workshop, attendees will set up their own project on one of the 
platforms, and be guided in the steps, from set-up to extracting and 
analyzing the crowdworkers’ results.

2) Crowdsourcing as a method that is both cheaper and more efficient 
than manual content analysis. Can it also be as valid and reliable? 
Research presentations on both “crowdcoding” and traditional manual 
coding will be given, as well as a discussion about cost structure and 
features to ensure quality results. The Speakers/Panelists include:

Hajo Boomgaarden, Professor of empirical social science method, 
University of Vienna

Brendan Watson, Assistant professor of journalism, Michigan State University

Lei Guo, Assistant professor of emerging media studies, Boston University

Margrit Betke, Professor of computer science, Boston University

Kate Mays, Ph.D. student in emerging media studies, Boston University


This is a half-day preconference. For questions, contact Dr. Lei Guo 
((guolei /at/ bu.edu) <mailto:(guolei /at/ bu.edu)>).

To register, follow this link: 
<http://www.icahdq.org/event/PC24_Crowdsourcing>.
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