Fortunato S, Flammini A, Menczer F, Vespignani A
School of Informatics, Department of Computer Science, Indiana University, Bloomington, IN 47406, USA.
Proc Natl Acad Sci U S A. 2006 Aug 22;103(34):12684-9. doi: 10.1073/pnas.0605525103. Epub 2006 Aug 10.
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.
搜索引擎已成为我们科学、经济和社会活动的关键媒介，它使人们能够在网络规模庞大且复杂的情况下访问信息。不利的一面是，搜索引擎根据其页面排名策略使流量偏向某些用户，并且有人认为它们制造了一个恶性循环，加剧了已确立且已广受欢迎的网站的主导地位。这种偏向可能导致危险的信息垄断。我们表明，与直觉相反，实证数据并不支持这一结论；热门网站获得的流量远低于预期。我们讨论了一个模型，该模型除了考虑搜索引擎对页面的排名方式外，还通过考虑用户的主题兴趣及其搜索行为来准确预测流量数据模式。用户兴趣的异质性解释了所观察到的搜索引擎流行度偏向的缓解情况。
