The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
The stochastic approach for link-structure analysis (SALSA) and the TKC effect
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Algorithm Design
Optimizing web search using social annotations
Proceedings of the 16th international conference on World Wide Web
iLink: search and routing in social networks
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Personalized social search based on the user's social network
Proceedings of the 18th ACM conference on Information and knowledge management
A sketch-based distance oracle for web-scale graphs
Proceedings of the third ACM international conference on Web search and data mining
The anatomy of a large-scale social search engine
Proceedings of the 19th international conference on World wide web
Partitioned multi-indexing: bringing order to social search
Proceedings of the 21st international conference on World Wide Web
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The proliferation of social media has the potential for changing the structure and organization of the web. In the past, scientists have looked at the web as a large connected component to understand how the topology of hyperlinks correlates with the quality of information contained in the page and they proposed techniques to rank information contained in web pages. We argue that information from web pages and network data on social relationships can be combined to create a personalized and socially connected web. In this paper, we look at the web as a composition of two networks, one consisting of information in web pages and the other of personal data shared on social media web sites. Together, they allow us to analyze how social media tunnels the flow of information from person to person and how to use the structure of the social network to rank, deliver, and organize information specifically for each individual user. We validate our social ranking concepts through a ranking experiment conducted on web pages that users shared on Google Buzz and Twitter.