Name
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. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2396761.2398689 | CIKM |
Keywords | Field | DocType |
online advertising,web search engine,crowdsourced approach,major web search engine,demotion strategy,indicative query,content farm article,suspect quality,search engine,web search,content farm,crowdsourcing,content farms | Data mining,World Wide Web,Search engine,Information retrieval,Demotion,Computer science,Crowdsourcing,Content farm,Online advertising,Suspect | Conference |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Richard Mccreadie | 1 | 403 | 32.43 |
| Craig Macdonald | 2 | 2588 | 178.50 |
| Iadh Ounis | 3 | 3438 | 234.59 |
| Jim Giles | 4 | 0 | 0.34 |
| Ferris Jabr | 5 | 0 | 0.34 |