The Rise of China in the International Trade Network: A Community Core Detection Approach
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{"title"=>"The rise of China in the international trade network: A community core detection approach", "type"=>"journal", "authors"=>[{"first_name"=>"Zhen", "last_name"=>"Zhu", "scopus_author_id"=>"56643462200"}, {"first_name"=>"Federica", "last_name"=>"Cerina", "scopus_author_id"=>"55232245500"}, {"first_name"=>"Alessandro", "last_name"=>"Chessa", "scopus_author_id"=>"6604050350"}, {"first_name"=>"Guido", "last_name"=>"Caldarelli", "scopus_author_id"=>"55139905100"}, {"first_name"=>"Massimo", "last_name"=>"Riccaboni", "scopus_author_id"=>"6603650921"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"373787388", "isbn"=>"19326203", "issn"=>"19326203", "arxiv"=>"arXiv:1404.6950v1", "doi"=>"10.1371/journal.pone.0105496", "scopus"=>"2-s2.0-84929354790", "pmid"=>"25136895", "sgr"=>"84929354790"}, "id"=>"e634bbcb-529d-339c-ac17-c14e093f82bc", "abstract"=>"Theory of complex networks proved successful in the description of a variety of complex systems ranging from biology to computer science and to economics and finance. Here we use network models to describe the evolution of a particular economic system, namely the International Trade Network (ITN). Previous studies often assume that globalization and regionalization in international trade are contradictory to each other. We re-examine the relationship between globalization and regionalization by viewing the international trade system as an interdependent complex network. We use the modularity optimization method to detect communities and community cores in the ITN during the years 1995-2011. We find rich dynamics over time both inter- and intra-communities. In particular, the Asia-Oceania community disappeared and reemerged over time along with a switch in leadership from Japan to China. We provide a multilevel description of the evolution of the network where the global dynamics (i.e., communities disappear or reemerge) and the regional dynamics (i.e., community core changes between community members) are related. Moreover, simulation results show that the global dynamics can be generated by a simple dynamic-edge-weight mechanism.", "link"=>"http://www.mendeley.com/research/rise-china-international-trade-network-community-core-detection-approach-6", "reader_count"=>24, "reader_count_by_academic_status"=>{"Researcher"=>8, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>9, "Student > Master"=>2, "Student > Bachelor"=>1, "Lecturer"=>1, "Professor"=>2}, "reader_count_by_user_role"=>{"Researcher"=>8, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>9, "Student > Master"=>2, "Student > Bachelor"=>1, "Lecturer"=>1, "Professor"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>4, "Engineering"=>1, "Mathematics"=>1, "Agricultural and Biological Sciences"=>1, "Veterinary Science and Veterinary Medicine"=>1, "Business, Management and Accounting"=>1, "Physics and Astronomy"=>4, "Social Sciences"=>5, "Earth and Planetary Sciences"=>1, "Economics, Econometrics and Finance"=>5}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Social Sciences"=>{"Social Sciences"=>5}, "Physics and Astronomy"=>{"Physics and Astronomy"=>4}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>1}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>5}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>1}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>1}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>4}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>1}}, "reader_count_by_country"=>{"China"=>1, "Italy"=>1, "Switzerland"=>1}, "group_count"=>10}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1641788"], "description"=>"<p>The figure is based on a single trial of simulation. Different colors represent different communities detected by the Newman-Girvan method. The inter-community edges are colored red while the intra-community ones are colored black. Although the community detection takes into account the edge weights, all the edges in the figure have the same width. In period 1, three predetermined communities, X1-X5, X6-X10, and X11-X15, are imposed in the network. The number of communities detected in this 15-node network bounces back and forth between 3 and 2 during the simulated periods. That is, like what we observe from the ITN, the disappearance and reemergence of the communities can be generated by the dynamic-edge-weight mechanism for both inter- and intra-communities.</p>", "links"=>[], "tags"=>["International Trade Network", "dynamic", "Community Core Detection Approach Theory", "community members", "Previous studies", "computer science", "simulation results show", "community cores", "modularity optimization method", "itn", "trade system", "use network models"], "article_id"=>1144576, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Zhen Zhu", "Federica Cerina", "Alessandro Chessa", "Guido Caldarelli", "Massimo Riccaboni"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0105496.g003", "stats"=>{"downloads"=>0, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_A_Detailed_Example_/1144576", "title"=>"A Detailed Example.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-08-19 02:52:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/1641791"], "description"=>"<p>This table has all the effective RTAs involving China during 1995–2011. (G) stands for Goods and (S) for Services. The data is extracted from the WTO website, <a href=\"http://rtais.wto.org/UI/PublicAllRTAList.aspx\" target=\"_blank\">http://rtais.wto.org/UI/PublicAllRTAList.aspx</a>.</p>", "links"=>[], "tags"=>["International Trade Network", "dynamic", "Community Core Detection Approach Theory", "community members", "Previous studies", "computer science", "simulation results show", "community cores", "modularity optimization method", "itn", "trade system", "use network models"], "article_id"=>1144579, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Zhen Zhu", "Federica Cerina", "Alessandro Chessa", "Guido Caldarelli", "Massimo Riccaboni"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0105496.t001", "stats"=>{"downloads"=>4, "page_views"=>22, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_China_s_Effective_RTAs_/1144579", "title"=>"China's Effective RTAs.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-08-19 02:52:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/1641792", "https://ndownloader.figshare.com/files/1641793"], "description"=>"<div><p>Theory of complex networks proved successful in the description of a variety of complex systems ranging from biology to computer science and to economics and finance. Here we use network models to describe the evolution of a particular economic system, namely the International Trade Network (ITN). Previous studies often assume that globalization and regionalization in international trade are contradictory to each other. We re-examine the relationship between globalization and regionalization by viewing the international trade system as an interdependent complex network. We use the modularity optimization method to detect communities and community cores in the ITN during the years 1995–2011. We find rich dynamics over time both inter- and intra-communities. In particular, the Asia-Oceania community disappeared and reemerged over time along with a switch in leadership from Japan to China. We provide a multilevel description of the evolution of the network where the global dynamics (i.e., communities disappear or reemerge) and the regional dynamics (i.e., community core changes between community members) are related. Moreover, simulation results show that the global dynamics can be generated by a simple dynamic-edge-weight mechanism.</p></div>", "links"=>[], "tags"=>["International Trade Network", "dynamic", "Community Core Detection Approach Theory", "community members", "Previous studies", "computer science", "simulation results show", "community cores", "modularity optimization method", "itn", "trade system", "use network models"], "article_id"=>1144580, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Zhen Zhu", "Federica Cerina", "Alessandro Chessa", "Guido Caldarelli", "Massimo Riccaboni"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0105496.s001", "https://dx.doi.org/10.1371/journal.pone.0105496.s002"], "stats"=>{"downloads"=>2, "page_views"=>16, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_Rise_of_China_in_the_International_Trade_Network_A_Community_Core_Detection_Approach_/1144580", "title"=>"The Rise of China in the International Trade Network: A Community Core Detection Approach", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2014-08-19 02:52:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/1641789"], "description"=>"<p>We calculate the ratio of the inter-community trade to the intra-community trade between the Asia-Oceania community and the America community. The ratio first went up and then went down and formed a hump shape over time. This finding coincides with the disappearance and reemergence of the Asia-Oceania community observed in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0105496#pone-0105496-g001\" target=\"_blank\">Figure 1</a>.</p>", "links"=>[], "tags"=>["International Trade Network", "dynamic", "Community Core Detection Approach Theory", "community members", "Previous studies", "computer science", "simulation results show", "community cores", "modularity optimization method", "itn", "trade system", "use network models"], "article_id"=>1144577, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Zhen Zhu", "Federica Cerina", "Alessandro Chessa", "Guido Caldarelli", "Massimo Riccaboni"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0105496.g004", "stats"=>{"downloads"=>1, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Inter_versus_Intra_Community_Trade_Ratio_between_Asia_Oceania_and_America_/1144577", "title"=>"Inter- versus Intra-Community Trade Ratio between Asia-Oceania and America.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-08-19 02:52:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/1641790"], "description"=>"<p>We calculate both the inter- and intra-community trade volumes for Japan and China. Japan had more inter-community trade than China before 2003. However, after 2003, China surpassed Japan in terms of both inter- and intra-community trade. This finding coincides with the leadership change from Japan to China observed in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0105496#pone-0105496-g001\" target=\"_blank\">Figure 1</a>. Furthermore, for both countries, the intra-community trade follows closely to the inter-community trade, which can be viewed as evidence of the intra-community dynamic-edge-weight mechanism.</p>", "links"=>[], "tags"=>["International Trade Network", "dynamic", "Community Core Detection Approach Theory", "community members", "Previous studies", "computer science", "simulation results show", "community cores", "modularity optimization method", "itn", "trade system", "use network models"], "article_id"=>1144578, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Zhen Zhu", "Federica Cerina", "Alessandro Chessa", "Guido Caldarelli", "Massimo Riccaboni"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0105496.g005", "stats"=>{"downloads"=>2, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Intra_and_Inter_Community_Strength_of_Japan_and_China_/1144578", "title"=>"Intra- and Inter-Community Strength of Japan and China.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-08-19 02:52:42"}

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