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Analysis of Search and Browsing Behavior of Young Users on the Web
ACM Transactions on the Web (TWEB)
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Though children frequently use web search engines to learn, interact, and be entertained, modern web search engines are poorly suited to children's needs, requiring relatively complex querying and filtering of results in order to find pages oriented to young audiences. To address this limitation, we designed AgeRank, a link-based algorithm that ranks web pages according their appropriateness for young audiences. We show its effectiveness through a multipart evaluation that demonstrates AgeRank to be accurate in page-labeling, widely-spanning in page coverage, and with high potential to improve children's search. As a fast, scalable, and effective algorithm, AgeRank can be adopted by search engines seeking to more effectively address the needs of young users, or easily fitted to complementary machine-learning based classification approaches.