Investigating relationships within and between category networks in Wikipedia
► Topology of Wikipedia citation network is not uniform. ► Connectivity patterns inside each category are different among themselves. ► The growth mechanisms of the categories are not equal. ► Full Wikipedia network analysis cannot predict the behaviour of isolated categories. This work maps and ana...
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description | ► Topology of Wikipedia citation network is not uniform. ► Connectivity patterns inside each category are different among themselves. ► The growth mechanisms of the categories are not equal. ► Full Wikipedia network analysis cannot predict the behaviour of isolated categories.
This work maps and analyses cross-citations in the areas of
Biology,
Mathematics,
Physics and
Medicine in the English version of Wikipedia, which are represented as an undirected complex network where the entries correspond to nodes and the citations among the entries are mapped as edges. We found a high value of clustering coefficient for the areas of
Biology and
Medicine, and a small value for
Mathematics and
Physics. The topological organization is also different for each network, including a modular structure for
Biology and
Medicine, a sparse structure for
Mathematics and a dense core for
Physics. The networks have degree distributions that can be approximated by a power-law with a cut-off. The assortativity of the isolated networks has also been investigated and the results indicate distinct patterns for each subject. We estimated the betweenness centrality of each node considering the full Wikipedia network, which contains the nodes of the four subjects and the edges between them. In addition, the average shortest path length between the subjects revealed a close relationship between the subjects of
Biology and
Physics, and also between
Medicine and
Physics. Our results indicate that the analysis of the full Wikipedia network cannot predict the behavior of the isolated categories since their properties can be very different from those observed in the full network. |
doi_str_mv | 10.1016/j.joi.2011.03.003 |
format | Article |
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This work maps and analyses cross-citations in the areas of
Biology,
Mathematics,
Physics and
Medicine in the English version of Wikipedia, which are represented as an undirected complex network where the entries correspond to nodes and the citations among the entries are mapped as edges. We found a high value of clustering coefficient for the areas of
Biology and
Medicine, and a small value for
Mathematics and
Physics. The topological organization is also different for each network, including a modular structure for
Biology and
Medicine, a sparse structure for
Mathematics and a dense core for
Physics. The networks have degree distributions that can be approximated by a power-law with a cut-off. The assortativity of the isolated networks has also been investigated and the results indicate distinct patterns for each subject. We estimated the betweenness centrality of each node considering the full Wikipedia network, which contains the nodes of the four subjects and the edges between them. In addition, the average shortest path length between the subjects revealed a close relationship between the subjects of
Biology and
Physics, and also between
Medicine and
Physics. Our results indicate that the analysis of the full Wikipedia network cannot predict the behavior of the isolated categories since their properties can be very different from those observed in the full network.</description><identifier>ISSN: 1751-1577</identifier><identifier>EISSN: 1875-5879</identifier><identifier>DOI: 10.1016/j.joi.2011.03.003</identifier><language>eng</language><publisher>Elsevier Ltd</publisher><subject>Citation analysis ; Complex network ; Encyclopaedias ; Map of science ; Science ; Wikipedia ; Wikis</subject><ispartof>Journal of informetrics, 2011-07, Vol.5 (3), p.431-438</ispartof><rights>2011 Elsevier Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c329t-3af05149fd6d59245548c065cef8946071380ef4de0588ee532333ca1dc974783</citedby><cites>FETCH-LOGICAL-c329t-3af05149fd6d59245548c065cef8946071380ef4de0588ee532333ca1dc974783</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.joi.2011.03.003$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,778,782,3539,27913,27914,45984</link.rule.ids></links><search><creatorcontrib>Silva, F.N.</creatorcontrib><creatorcontrib>Viana, M.P.</creatorcontrib><creatorcontrib>Travençolo, B.A.N.</creatorcontrib><creatorcontrib>Costa, L. da F.</creatorcontrib><title>Investigating relationships within and between category networks in Wikipedia</title><title>Journal of informetrics</title><description>► Topology of Wikipedia citation network is not uniform. ► Connectivity patterns inside each category are different among themselves. ► The growth mechanisms of the categories are not equal. ► Full Wikipedia network analysis cannot predict the behaviour of isolated categories.
This work maps and analyses cross-citations in the areas of
Biology,
Mathematics,
Physics and
Medicine in the English version of Wikipedia, which are represented as an undirected complex network where the entries correspond to nodes and the citations among the entries are mapped as edges. We found a high value of clustering coefficient for the areas of
Biology and
Medicine, and a small value for
Mathematics and
Physics. The topological organization is also different for each network, including a modular structure for
Biology and
Medicine, a sparse structure for
Mathematics and a dense core for
Physics. The networks have degree distributions that can be approximated by a power-law with a cut-off. The assortativity of the isolated networks has also been investigated and the results indicate distinct patterns for each subject. We estimated the betweenness centrality of each node considering the full Wikipedia network, which contains the nodes of the four subjects and the edges between them. In addition, the average shortest path length between the subjects revealed a close relationship between the subjects of
Biology and
Physics, and also between
Medicine and
Physics. Our results indicate that the analysis of the full Wikipedia network cannot predict the behavior of the isolated categories since their properties can be very different from those observed in the full network.</description><subject>Citation analysis</subject><subject>Complex network</subject><subject>Encyclopaedias</subject><subject>Map of science</subject><subject>Science</subject><subject>Wikipedia</subject><subject>Wikis</subject><issn>1751-1577</issn><issn>1875-5879</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><recordid>eNp1kM1OwzAQhC0EEqXwANxy45SwjuPYESdU8VOpiAuIo2WcTes0dYKdturb46pcOe1oNbPa-Qi5pZBRoOV9m7W9zXKgNAOWAbAzMqFS8JRLUZ1HLThNKRfiklyF0ALwsqTVhLzN3Q7DaJd6tG6ZeOyi6F1Y2SEkezuurEu0q5NvHPeILjF6xGXvD4mLi96vQxINX3ZtB6ytviYXje4C3vzNKfl8fvqYvaaL95f57HGRGpZXY8p0A5wWVVOXNa_ygvNCGii5wUZWRQmCMgnYFDUClxKRs5wxZjStTSUKIdmU3J3uDr7_2cb_1cYGg12nHfbboCrIoSwYz6OTnpzG9yF4bNTg7Ub7g6KgjuRUqyI5dSSngKlILmYeThmMFXYWvQrGojOxoUczqjr6_0__Al5ydro</recordid><startdate>20110701</startdate><enddate>20110701</enddate><creator>Silva, F.N.</creator><creator>Viana, M.P.</creator><creator>Travençolo, B.A.N.</creator><creator>Costa, L. da F.</creator><general>Elsevier Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>E3H</scope><scope>F2A</scope></search><sort><creationdate>20110701</creationdate><title>Investigating relationships within and between category networks in Wikipedia</title><author>Silva, F.N. ; Viana, M.P. ; Travençolo, B.A.N. ; Costa, L. da F.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c329t-3af05149fd6d59245548c065cef8946071380ef4de0588ee532333ca1dc974783</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Citation analysis</topic><topic>Complex network</topic><topic>Encyclopaedias</topic><topic>Map of science</topic><topic>Science</topic><topic>Wikipedia</topic><topic>Wikis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Silva, F.N.</creatorcontrib><creatorcontrib>Viana, M.P.</creatorcontrib><creatorcontrib>Travençolo, B.A.N.</creatorcontrib><creatorcontrib>Costa, L. da F.</creatorcontrib><collection>CrossRef</collection><collection>Library & Information Sciences Abstracts (LISA)</collection><collection>Library & Information Science Abstracts (LISA)</collection><jtitle>Journal of informetrics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Silva, F.N.</au><au>Viana, M.P.</au><au>Travençolo, B.A.N.</au><au>Costa, L. da F.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Investigating relationships within and between category networks in Wikipedia</atitle><jtitle>Journal of informetrics</jtitle><date>2011-07-01</date><risdate>2011</risdate><volume>5</volume><issue>3</issue><spage>431</spage><epage>438</epage><pages>431-438</pages><issn>1751-1577</issn><eissn>1875-5879</eissn><abstract>► Topology of Wikipedia citation network is not uniform. ► Connectivity patterns inside each category are different among themselves. ► The growth mechanisms of the categories are not equal. ► Full Wikipedia network analysis cannot predict the behaviour of isolated categories.
This work maps and analyses cross-citations in the areas of
Biology,
Mathematics,
Physics and
Medicine in the English version of Wikipedia, which are represented as an undirected complex network where the entries correspond to nodes and the citations among the entries are mapped as edges. We found a high value of clustering coefficient for the areas of
Biology and
Medicine, and a small value for
Mathematics and
Physics. The topological organization is also different for each network, including a modular structure for
Biology and
Medicine, a sparse structure for
Mathematics and a dense core for
Physics. The networks have degree distributions that can be approximated by a power-law with a cut-off. The assortativity of the isolated networks has also been investigated and the results indicate distinct patterns for each subject. We estimated the betweenness centrality of each node considering the full Wikipedia network, which contains the nodes of the four subjects and the edges between them. In addition, the average shortest path length between the subjects revealed a close relationship between the subjects of
Biology and
Physics, and also between
Medicine and
Physics. Our results indicate that the analysis of the full Wikipedia network cannot predict the behavior of the isolated categories since their properties can be very different from those observed in the full network.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.joi.2011.03.003</doi><tpages>8</tpages></addata></record> |
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subjects | Citation analysis Complex network Encyclopaedias Map of science Science Wikipedia Wikis |
title | Investigating relationships within and between category networks in Wikipedia |
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