Topical interests and the mitigation of search engine bias
Topical interests and the mitigation of search engine bias
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DOI：
10.1073/pnas.0605525103
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发表时间：
2006-08-22
影响因子：
11.1
通讯作者：
Vespignani, A.
中科院分区：
文献类型：
--
作者：
Fortunato, S.;Flammini, A.;Vespignani, A.
搜索引擎已经成为我们的科学，经济和社会活动的关键媒体，使人们能够访问网络上的信息，尽管它的大小和复杂性。不利的一面是，搜索引擎根据其页面排名策略对用户的流量产生偏见，有人认为，它们创造了一个恶性循环，放大了已建立和已经流行的网站的主导地位。这种偏见可能导致对信息的危险垄断。我们发现，与直觉相反，经验数据并不支持这一结论，热门网站收到的流量远远低于预测。我们讨论了一个模型，考虑到用户的主题兴趣和他们的搜索行为，除了搜索引擎排名页面的方式，准确地预测流量数据模式。用户兴趣的异质性解释了观察到的搜索引擎流行度偏差的缓解。
Search engines have become key media for our scientific, economic, and social activities by enabling people to access information on the web despite its size and complexity. On the down side, search engines bias the traffic of users according to their page ranking strategies, and it has been argued that they create a vicious cycle that amplifies the dominance of established and already popular sites. This bias could lead to a dangerous monopoly of information. We show that, contrary to intuition, empirical data do not support this conclusion; popular sites receive far less traffic than predicted. We discuss a model that accurately predicts traffic data patterns by taking into consideration the topical interests of users and their searching behavior in addition to the way search engines rank pages. The heterogeneity of user interests explains the observed mitigation of search engines' popularity bias.