An examination of content farms in web search using crowdsourcing

Authors:
Richard McCreadie;Craig Macdonald;Iadh Ounis;Jim Giles;Ferris Jabr
Affiliations:
University of Glasgow, Glasgow, United Kingdom;University of Glasgow, Glasgow, United Kingdom;University of Glasgow, Glasgow, United Kingdom;New Scientist, San Francisco, USA;New Scientist, Waltham, USA
Venue:
Proceedings of the 21st ACM international conference on Information and knowledge management
Year:
2012

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Abstract

On the Web, content farms produce articles engineered such that search engines rank them highly, in order to turn a profit from online advertising. Recently, content farms have increasingly been the target of demotion strategies by Web search engines, since content farm articles are often considered to be of suspect quality. In this paper, we study the prevalence of content farms in the results returned by three major Web search engines over time. In particular, we develop a crowdsourced approach to identify content farm articles from the results returned by these search engines. Our results show that between the period of March and August 2011, the number of content farm articles observed on a number of indicative queries was reduced by up to 55% in the top ranks.