%0 Journal Article
%T 复杂网络视角下RCEP与CPTPP自贸协定规则文本关联性分析<br>Analysis of the Relevance of RCEP and CPTPP FTA Rule Texts under the Perspective of Complex Networks
%A 吕坤阳
%A 朱小栋
%J Operations Research and Fuzziology
%P 299-308
%@ 2163-1530
%D 2024
%I Hans Publishing
%R 10.12677/ORF.2024.141029
%X 加入《全面与进步跨太平洋伙伴关系协定》(CPTPP)是中国在新时代扩大对外开放的重要举措，也表示着中国积极参与全球化经济建设的决心。本文以复杂网络视角研究了中国已签署的经贸规模最大的自贸协定《区域全面经济伙伴关系协定》(RCEP)与CPTPP自贸协定规则文本之间的关联性，对于了解中国申请加入CPTPP仍需努力的方向具有一定现实意义。本文结合了复杂网络与文本分析方法，通过构建关键词网络测算了网络的度中心性、接近中心性以及介数中心性等测度指标。研究发现，CPTPP相较于RCEP所涉及的范围更加全面且严格，文本结构以及稳定性也高于RCEP，但RCEP对于附属章节的设置更为详尽。并且RCEP与CPTPP法律约束力相差不大，都属于高法律约束力自贸协定。且RCEP与CPTPP在自贸协定文本中一体化议题侧重点及标准差别明显。<br />
Joining the Comprehensive and Progressive Trans-Pacific Partnership (CPTPP) is an important step for China to expand its openness to the outside world in the new era, and it also expresses China’s determination to actively participate in the construction of globalized economy. This paper studies the correlation between the Regional Comprehensive Economic Partnership (RCEP), the largest FTA in terms of economic and trade scale that China has signed, and the text of CPTPP FTA rules from a complex network perspective, which is of some practical significance for understanding the direction that China still needs to work on in order to apply for joining CPTPP. This paper combines complex network and text analysis methods, and measures the degree centrality, proximity centrality and median centrality of the network by constructing a keyword network. It is found that the scope of CPTPP is more comprehensive and strict than that of RCEP, and the structure and stability of the text is higher than that of RCEP, but RCEP is more detailed for the setting of subsidiary chapters. And RCEP and CPTPP are not much different from each other in terms of legal binding force; both belong to high legally binding FTAs. And RCEP and CPTPP in the FTA text integration issues focus and standards differ significantly.
%K 自贸协定，复杂网络，文本分析，共词矩阵，共现网络<br>FTA
%K Complex Network
%K Text Analysis
%K Co-Word Matrix
%K Co-Occurrence Network
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=81135