Detecting emerging research fronts in regenerative medicine by the citation network analysis of scientific publications
In this paper, we detect emerging research fronts in a huge number of academic papers related to regenerative medicine, a field of radically innovative research. We divide citation networks into clusters using the topological clustering method, track the positions of papers in each cluster, and visu...
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| Veröffentlicht in: | Technological forecasting & social change 2011-02, Vol.78 (2), p.274-282 |
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| creator | Shibata, Naoki Kajikawa, Yuya Takeda, Yoshiyuki Sakata, Ichiro Matsushima, Katsumori |
| description | In this paper, we detect emerging research fronts in a huge number of academic papers related to regenerative medicine, a field of radically innovative research. We divide citation networks into clusters using the topological clustering method, track the positions of papers in each cluster, and visualize citation networks with characteristic terms for each cluster. Analyzing the clustering results with the average published year and parent–child relationship of each cluster could be helpful in detecting recent trends. In addition, tracking topological measures, within-cluster degree
z and participation coefficient
P, enables us to determine whether there are emerging knowledge clusters. Our results show the success of our method in detecting emerging research fronts in regenerative medicine, and these results are confirmed as reasonable by experts. Finally, we predict the future core papers, with the potential of many citations, via the betweenness centralities in the citation network of the research into adult and somatic stem cells. |
| doi_str_mv | 10.1016/j.techfore.2010.07.006 |
| format | Article |
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z and participation coefficient
P, enables us to determine whether there are emerging knowledge clusters. Our results show the success of our method in detecting emerging research fronts in regenerative medicine, and these results are confirmed as reasonable by experts. Finally, we predict the future core papers, with the potential of many citations, via the betweenness centralities in the citation network of the research into adult and somatic stem cells.</description><identifier>ISSN: 0040-1625</identifier><identifier>EISSN: 1873-5509</identifier><identifier>DOI: 10.1016/j.techfore.2010.07.006</identifier><identifier>CODEN: TFSCB3</identifier><language>eng</language><publisher>New York: Elsevier Inc</publisher><subject>Centrality ; Citation analysis ; Cluster analysis ; Clusters ; Embryonic stem cells ; Emerging topic detection ; Induced pluripotent stem cells ; Knowledge ; Medical research ; Medicine ; Network Analysis ; Networks ; Parent Child Relations ; Participation ; Regeneration (physiology) ; Regenerative medicine ; Research front ; Scholarly publishing ; Scientific papers ; Stem cells ; Studies ; Topology ; Tracking (position)</subject><ispartof>Technological forecasting & social change, 2011-02, Vol.78 (2), p.274-282</ispartof><rights>2010 Elsevier Inc.</rights><rights>Copyright Elsevier Science Ltd. Feb 2011</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c696t-46d5dce2157ef636676c0e3d68bfe1fd9ee09cbb4e6ad5b91f73a4e63cee664c3</citedby><cites>FETCH-LOGICAL-c696t-46d5dce2157ef636676c0e3d68bfe1fd9ee09cbb4e6ad5b91f73a4e63cee664c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S004016251000154X$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,33751,33752,65306</link.rule.ids></links><search><creatorcontrib>Shibata, Naoki</creatorcontrib><creatorcontrib>Kajikawa, Yuya</creatorcontrib><creatorcontrib>Takeda, Yoshiyuki</creatorcontrib><creatorcontrib>Sakata, Ichiro</creatorcontrib><creatorcontrib>Matsushima, Katsumori</creatorcontrib><title>Detecting emerging research fronts in regenerative medicine by the citation network analysis of scientific publications</title><title>Technological forecasting & social change</title><description>In this paper, we detect emerging research fronts in a huge number of academic papers related to regenerative medicine, a field of radically innovative research. We divide citation networks into clusters using the topological clustering method, track the positions of papers in each cluster, and visualize citation networks with characteristic terms for each cluster. Analyzing the clustering results with the average published year and parent–child relationship of each cluster could be helpful in detecting recent trends. In addition, tracking topological measures, within-cluster degree
z and participation coefficient
P, enables us to determine whether there are emerging knowledge clusters. Our results show the success of our method in detecting emerging research fronts in regenerative medicine, and these results are confirmed as reasonable by experts. 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z and participation coefficient
P, enables us to determine whether there are emerging knowledge clusters. Our results show the success of our method in detecting emerging research fronts in regenerative medicine, and these results are confirmed as reasonable by experts. Finally, we predict the future core papers, with the potential of many citations, via the betweenness centralities in the citation network of the research into adult and somatic stem cells.</abstract><cop>New York</cop><pub>Elsevier Inc</pub><doi>10.1016/j.techfore.2010.07.006</doi><tpages>9</tpages></addata></record> |
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| source | Elsevier ScienceDirect Journals; Sociological Abstracts |
| subjects | Centrality Citation analysis Cluster analysis Clusters Embryonic stem cells Emerging topic detection Induced pluripotent stem cells Knowledge Medical research Medicine Network Analysis Networks Parent Child Relations Participation Regeneration (physiology) Regenerative medicine Research front Scholarly publishing Scientific papers Stem cells Studies Topology Tracking (position) |
| title | Detecting emerging research fronts in regenerative medicine by the citation network analysis of scientific publications |
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