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Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems

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Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems ( online-social-networks-measurement-analysis-and-applications )

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202 Independent of the content, users maintain links to other users, which indicate trust or shared interest. Locating The predominant method of finding information in online social networks is to nav- igate through the social network, browsing content introduced or recommended by other users. Some sites also provide keyword-based search for textual or tagged con- tent. Additionally, other sites have ‘top-10’ lists showing the most popular content, where the popularity is determined according to how often users have accessed the content or based on explicit recommendations provided by users. Moreover, social networks enable users to find timely, relevant and reliable infor- mation. This is because users can browse adjacent regions of their social network, which likely consist of users with shared interests or mutual trust. Since the content can be non-textual, obscure, or short-lived, it may be hard to find by the way of Web search. For example, blog posts are generally of short-term interest, videos and pho- tos are non-textual, and all three types of content tend to be of interest to a limited audience. Content in social networks can also be rated rapidly, based on implicit and explicit feedback of a large community of content consumers. In contrast, Web search relies on the slower process of discovering hyperlinks in the Web, which are created by a relatively smaller number of content authors. Since content rating in social networks

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