friends-on-the-web - Friends and Neighbors on the Web Lada...

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Friends and Neighbors on the Web Lada A. Adamic Xerox PARC 3333 Coyote Hill Rd. Palo Alto, CA 94304 (650) 812-4778 [email protected] Eytan Adar HP Sand Hill Laboratory* 1501 Page Mill Road M/S 1U-19 Palo Alto, CA 94304 (650) 857-2398 [email protected] ABSTRACT The Internet has become a rich and large repository of information about us as individuals. Anything from the links and text on a user's homepage to the mailing lists the user subscribes to are reflections of social interactions a user has in the real world. In this paper we devise techniques to mine this information in order to predict relationships between individuals. Further we show that some pieces of information are better indicators of social connections than others, and that these indicators vary between user populations and provide a glimpse into the social lives of individuals in different communities. Our techniques provide potential applications in automatically inferring real-world connections and discovering, labeling, and characterizing communities. Keywords Homepage analysis, social network, small worlds, web communities 1. INTRODUCTION One of the first large scale web applications was the serving of individual homepages. These generally autobiographical pages reflect a user ’s interests and experiences. They include anything from photographs of the user ’s pet to the user ’s essays or resume. Homepages are not free-floating in the web, but point to and are pointed at by other users, our "friends and neighbors" on the web. These links can represent anything from friendship, to collaboration, to general interest in the material on the other user ’s homepage. In this way individual homepages become part of a large community structure. Recent work [6] [7] [10] has attempted to use analysis of link topology to find "web communities." These web communities are web page collections with a shared topic. For example, any page dealing with 'data mining' and linking to other pages on the same topic would be part of the data mining page collection. Such a page is not necessarily a homepage or even associated with a particular individual. In contrast, our work focuses on individuals' homepages and the connections between them, essentially allowing us to tap into both virtual and real world communities of people. Although homepage identification has been researched as a separate problem [8][12], to our knowledge this is the first link analysis on a network of homepages. Rather than discarding the previous concept that pages which share a topic are likely to link to one another, we can now use it to characterize relationships between people. For example, are people who mention 'dance troupe' likely to link to each other? Consequently, can we use terms on homepages to predict where
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This note was uploaded on 05/27/2011 for the course CIS 4930 taught by Professor Staff during the Spring '08 term at University of Florida.

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friends-on-the-web - Friends and Neighbors on the Web Lada...

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