http://www.bibsonomy.org/burst/user/hotho/networksBibSonomy BuRST Feed for /user/hotho/networks2008-07-21T01:16:12+02:00http://www.bibsonomy.org/bibtex/256de7e6d214faebdbf2f2ef0fce09d7d/hothohotho2008-06-02T15:12:04+02:00fast clustering networks community algorithm <span style="color:#555555;">M.E.J. <a href="http://www.bibsonomy.org/author/Newman">Newman</a> </span><em>Physical Review E</em><em>September2003. </em>Mon Jun 02 15:12:04 CEST 2008Physical Review ESeptemberFast algorithm for detecting community structure in networks692003fast clustering networks community algorithm http://www.bibsonomy.org/bibtex/2738a4cffd8d031871c9c223f36b258f1/hothohotho2007-11-30T14:46:49+01:00social worlds networks sosbuch small <span style="color:#555555;">M.E.J. <a href="http://www.bibsonomy.org/author/Newman">Newman</a> </span><em>Complexity</em>(<em>2000</em>)Fri Nov 30 14:46:49 CET 2007ComplexitySmall Worlds: The Structure of Social Networks2000social worlds networks sosbuch small dblphttp://www.bibsonomy.org/bibtex/27efa21cb8537359f6995cde9c307d181/hothohotho2007-10-28T22:18:15+01:00graph communities toread soical networks dm clustering <span style="color:#555555;">Hemant <a href="http://www.bibsonomy.org/author/Balakrishnan">Balakrishnan</a> and Narsingh <a href="http://www.bibsonomy.org/author/Deo">Deo</a> </span><em>ACM Southeast Regional Conference, </em><em>page280-285. </em><em>ACM, </em>(<em>2006</em>)Sun Oct 28 22:18:15 CET 2007ACM Southeast Regional Conferenceconf/ACMse/2006280-285Discovering communities in complex networks.2006graph communities toread soical networks dm clustering [cond-mat/0408187] Finding community structure in very large networkshttp://www.bibsonomy.org/bibtex/20ea285bfc0f5a46ffec8a213e5133ba6/hothohotho2007-05-25T16:30:51+02:00community clustering large networks toread <span style="color:#555555;">Aaron <a href="http://www.bibsonomy.org/author/Clauset">Clauset</a> and M. E. J. <a href="http://www.bibsonomy.org/author/Newman">Newman</a> and Cristopher <a href="http://www.bibsonomy.org/author/Moore">Moore</a> </span><em>Physical Review E</em>(<em>2004</em>)Fri May 25 16:30:51 CEST 2007Physical Review E066111Finding community structure in very large networks702004community clustering large networks toread ScienceDirect - Physica A: Statistical and Theoretical Physics : Strong correlations between text quality and complex networks featureshttp://www.bibsonomy.org/bibtex/28fb247044a9326fd0f4d222d4dd4b4d8/hothohotho2006-11-21T19:37:21+01:00analysis Complex Text networks measurements Networks <span style="color:#555555;">L. <a href="http://www.bibsonomy.org/author/Antiqueira">Antiqueira</a> and M.G.V. <a href="http://www.bibsonomy.org/author/Nunes">Nunes</a> and O.N. <a href="http://www.bibsonomy.org/author/Oliveira Jr.">Oliveira Jr.</a> and L. <a href="http://www.bibsonomy.org/author/da F. Costa">da F. Costa</a> </span><em>Physica A: Statistical and Theoretical Physics</em><em>#jan#2007. </em>Tue Nov 21 19:37:21 CET 2006Physica A: Statistical and Theoretical Physics#jan#811--820Strong correlations between text quality and complex networks features3732007analysis Complex Text networks measurements Networks Concepts of complex networks have been used to obtain metrics that were correlated to text quality established by scores assigned by human judges. Texts produced by high-school students in Portuguese were represented as scale-free networks (word adjacency model), from which typical network features such as the in/outdegree, clustering coefficient and shortest path were obtained. Another metric was derived from the dynamics of the network growth, based on the variation of the number of connected components. The scores assigned by the human judges according to three text quality criteria (coherence and cohesion, adherence to standard writing conventions and theme adequacy/development) were correlated with the network measurements. Text quality for all three criteria was found to decrease with increasing average values of outdegrees, clustering coefficient and deviation from the dynamics of network growth. Among the criteria employed, cohesion and coherence showed the strongest correlation, which probably indicates that the network measurements are able to capture how the text is developed in terms of the concepts represented by the nodes in the networks. Though based on a particular set of texts and specific language, the results presented here point to potential applications in other instances of text analysis.http://www.bibsonomy.org/bibtex/27bf31320e8cb8d5db160085e17e80a93/hothohotho2006-03-31T07:35:24+02:00information oe networks email social extraction <span style="color:#555555;">A. <a href="http://www.bibsonomy.org/author/Culotta">Culotta</a> and R. <a href="http://www.bibsonomy.org/author/Bekkerman">Bekkerman</a> and <a href="http://www.bibsonomy.org/author/A.McCallum">A.McCallum</a> </span><em>Proc.\ Conference on Email and Anti-Spam (CEAS), </em><em>Mountain View, USA, </em><em>July2004. </em>Fri Mar 31 07:35:24 CEST 2006Mountain View, USAProc.\ Conference on Email and Anti-Spam (CEAS)July{Extracting social networks and contact information from email and the Web}2004information oe networks email social extraction http://www.bibsonomy.org/bibtex/2e38f8925480aefa240bb82abfd3df2d9/hothohotho2006-03-13T18:50:31+01:00tags folksonomy software networks social <span style="color:#555555;">Daniel <a href="http://www.bibsonomy.org/author/Chudnov">Chudnov</a> and Jeffrey <a href="http://www.bibsonomy.org/author/Barnett">Barnett</a> and Raman <a href="http://www.bibsonomy.org/author/Prasad">Prasad</a> and Matthew <a href="http://www.bibsonomy.org/author/Wilcox">Wilcox</a> </span><em>Library Hi Tech</em><em>23(4):469--480</em><em>January2005. </em>Mon Mar 13 18:50:31 CET 2006Library Hi TechJanuary4469--480Experiments in academic social book marking with Unalog232005tags folksonomy software networks social