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</script>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.
7 pages, ASONAM 2013
Social and Information Networks (cs.SI), FOS: Computer and information sciences, Physics - Physics and Society, FOS: Physical sciences, Computer Science - Social and Information Networks, Physics and Society (physics.soc-ph), Information Retrieval (cs.IR), Computer Science - Information Retrieval
Social and Information Networks (cs.SI), FOS: Computer and information sciences, Physics - Physics and Society, FOS: Physical sciences, Computer Science - Social and Information Networks, Physics and Society (physics.soc-ph), Information Retrieval (cs.IR), Computer Science - Information Retrieval
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 6 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
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| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
