Scatter networks: a new approach for analysing information scatter
dc.contributor.author | Adamic, Lada A. | en_US |
dc.contributor.author | Suresh, K. | en_US |
dc.contributor.author | Shi, Xiaolin | en_US |
dc.date.accessioned | 2008-04-02T14:49:25Z | |
dc.date.available | 2008-04-02T14:49:25Z | |
dc.date.issued | 2007-07-01 | en_US |
dc.identifier.citation | Adamic, Lada A; Suresh, K; Shi, Xiaolin (2007). "Scatter networks: a new approach for analysing information scatter." New Journal of Physics. 9(7): 231. <http://hdl.handle.net/2027.42/58170> | en_US |
dc.identifier.issn | 1367-2630 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/58170 | |
dc.description.abstract | Information on any given topic is often scattered across the Web. Previously this scatter has been characterized through the inequality of distribution of facts (i.e. pieces of information) across webpages. Such an approach conceals how specific facts (e.g. rare facts) occur in specific types of pages (e.g. fact-rich pages). To reveal such regularities, we construct bipartite networks, consisting of two types of vertices: the facts contained in webpages and the webpages themselves. Such a representation enables the application of a series of network analysis techniques, revealing structural features such as connectivity, robustness and clustering. Not only does network analysis yield new insights into information scatter, but we also illustrate the benefit of applying new and existing analysis techniques directly to a bipartite network as opposed to its one-mode projection. We discuss the implications of each network feature to the users’ ability to find comprehensive information online. Finally, we compare the bipartite graph structure of webpages and facts with the hyperlink structure between the webpages. | en_US |
dc.format.extent | 3118 bytes | |
dc.format.extent | 534034 bytes | |
dc.format.mimetype | text/plain | |
dc.format.mimetype | application/pdf | |
dc.publisher | IOP Publishing Ltd | en_US |
dc.title | Scatter networks: a new approach for analysing information scatter | en_US |
dc.type | Article | en_US |
dc.subject.hlbsecondlevel | Physics | en_US |
dc.subject.hlbtoplevel | Science | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | School of Information, University of Michigan, Ann Arbor, MI 48109, USA; | en_US |
dc.contributor.affiliationum | School of Information, University of Michigan, Ann Arbor, MI 48109, USA | en_US |
dc.contributor.affiliationum | Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/58170/2/njp7_7_231.pdf | |
dc.identifier.doi | http://dx.doi.org/10.1088/1367-2630/9/7/231 | en_US |
dc.identifier.source | New Journal of Physics. | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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