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数据分析与知识发现  2023, Vol. 7 Issue (10): 37-49     https://doi.org/10.11925/infotech.2096-3467.2022.0895
  研究论文 本期目录 | 过刊浏览 | 高级检索 |
药物领域三元闭包形成的影响机制研究——基于机会-信任-动机视角*
吴胜男1(),孙乙丹1,蒲虹君1,董继宗1,高健1,田若楠2,李霖1
1山西医科大学管理学院 太原 030001
2山西医科大学人文社会科学学院 太原 030001
Influencing Mechanisms of Triadic Closure in Pharmaceutical — Opportunity, Trust, and Motivation
Wu Shengnan1(),Sun Yidan1,Pu Hongjun1,Dong Jizong1,Gao Jian1,Tian Ruonan2,Li Lin1
1Shanxi Medical University School of Management, Taiyuan 030001,China
2Shanxi Medical University School of Humanities and Social Sciences, Taiyuan 030001,China
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摘要 

【目的】基于社交有向网络中影响三元闭包形成的机会、信任、动机三机制视角,深入探讨药物领域三元闭包形成的影响机制,为药物知识发现提供基础研究。【方法】借助社会网络指标测度机会、信任和动机三类机制,利用皮尔逊法检验三类机制与三元闭包边聚类系数及三元闭包数量的相关关系;并引入更多节点属性和网络特征,通过计量经济学的方法深入检验节点属性与网络特征对三类机制的影响作用。【结果】节点对机会与节点对边聚类系数呈强正相关性(r1>0.5);节点对信任、动机与节点对所在封闭三元组数目呈强正相关性(r3、r5>0.5);节点对邻近中心性对机会、信任具有负向影响作用,对动机具有正向影响作用;节点对中介中心性与特征向量中心性对机会、信任、动机均具有正向影响作用;网络平均路径长度对节点对机会具有负向影响作用,对节点对信任、动机具有正向影响作用。【局限】 选用的主题数据规模较小,未纳入大规模文献进行实证分析。【结论】提出的药物领域三元闭包形成三种影响机制均能较好地表现节点对三元闭包形成情况,并发现节点属性与网络特征对三机制具有影响作用,可为药物知识发现提供新的探索角度。

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吴胜男
孙乙丹
蒲虹君
董继宗
高健
田若楠
李霖
关键词 三元闭包聚类系数相关系数    
Abstract

[Objective] Opportunity, trust, and motivation are the three mechanisms influencing the formation of triadic closure in directed social networks. This paper explores the mechanisms affecting triadic closure in the pharmaceutical domain, aiming to provide foundations for drug knowledge discovery. [Methods] First, we used social network indices to measure the three mechanisms of opportunity, trust, and motivation. Then, we examined the Pearson correlation coefficient between these mechanisms and the triadic closure clustering and their numbers. Third, we introduced additional node attributes, network characteristics, and econometric methods to examine the relationships between node attributes and network characteristics/the three mechanisms. [Results] The node pairs for the opportunity and the clustering coefficient of the edges between them showed a strong positive correlation (r1>0.5). The node pairs for trust and motivation showed a strong positive correlation with the number of enclosed triads they belong to (r3, r5>0.5). The closeness centrality of node pairs negatively impacted the opportunity and trust,but a positive impact on motivation. The betweenness centrality and eigenvector centrality of node pairs positively impacted opportunity, trust, and motivation. The average path length of the network negatively affected the opportunity of node pairs but positively impacted their trust and motivation. [Limitations] More literature needs to be included for empirical analysis in the future. [Conclusions] The proposed method illustrates the circumstances of triadic closure formation for node pairs. Node attributes and network characteristics influence the three mechanisms, which provides a new direction for drug knowledge discovery.

Key wordsTriadic Closure    Clustering Coefficient    Correlation Coefficient
收稿日期: 2022-08-25      出版日期: 2023-03-28
ZTFLH:  G350  
基金资助:*国家自然科学基金青年项目(71804102);山西省高等学校哲学社会科学研究项目(2019W040);山西省研究生教育教学改革课题(2021YJJG115)
通讯作者: 吴胜男,ORCID: 0000-0003-1509-5244, E-mail: vivian_sxmu@163.com。   
引用本文:   
吴胜男, 孙乙丹, 蒲虹君, 董继宗, 高健, 田若楠, 李霖. 药物领域三元闭包形成的影响机制研究——基于机会-信任-动机视角*[J]. 数据分析与知识发现, 2023, 7(10): 37-49.
Wu Shengnan, Sun Yidan, Pu Hongjun, Dong Jizong, Gao Jian, Tian Ruonan, Li Lin. Influencing Mechanisms of Triadic Closure in Pharmaceutical — Opportunity, Trust, and Motivation. Data Analysis and Knowledge Discovery, 2023, 7(10): 37-49.
链接本文:  
https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.2096-3467.2022.0895      或      https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/Y2023/V7/I10/37
Fig.1  药物知识网络中三元闭包平衡结构
Fig.2  探讨药物领域中三元闭包形成的影响机制的研究思路
时间窗口 文献数量 主题词数量 连边数 网络全局聚类系数
1991-1993 12 60 672 0.627 3
1994-1996 25 111 1 249 0.474 3
1997-1999 53 188 2 178 0.301 1
2000-2002 100 303 4 438 0.290 3
2003-2005 113 361 5 711 0.278 5
2006-2008 182 521 8 629 0.2175
2009-2011 269 719 13 505 0.199 0
2012-2014 366 886 17 391 0.185 5
2015-2017 451 1 227 24 422 0.148 8
2018-2020 419 1 148 21 146 0.145 4
Table 1  各时间窗口网络数据特征及计算结果(1991-2020)
Fig.3  机会、信任值与边聚类系数相关性散点图
Fig.4  动机值与边聚类系数相关性散点图
时间窗口 节点对机会均值
o ( u i , u ) j ˉ
节点对机会与其边聚类系数的相关性r1 相关
显著性p1
1991-1993 0.495 8 0.996 6 0.000***
1994-1996 0.395 6 0.994 1 0.000***
1997-1999 0.300 8 0.998 0 0.000***
2000-2002 0.269 0 0.996 5 0.000***
2003-2005 0.274 7 0.997 7 0.000***
2006-2008 0.261 3 0.998 3 0.000***
2009-2011 0.227 2 0.997 8 0.000***
2012-2014 0.219 7 0.998 1 0.000***
2015-2017 0.207 0 0.998 4 0.000***
2018-2020 0.204 8 0.997 8 0.000***
Table 2  节点对机会均值以及r1计算结果
时间窗口 节点对信任均值
t ( u i , u ) j ˉ
节点对信任与其边聚集系数的相关性r2 相关显著性p2 节点对信任与节点对所在封闭三元组数目的相关性r3 相关显著性p3
1991-1993 14.393 2 0.189 9 0.000*** 0.921 6 0.000***
1994-1996 15.795 7 0.050 9 0.000*** 0.961 9 0.000***
1997-1999 18.173 9 0.047 3 0.000*** 0.972 3 0.000***
2000-2002 26.898 2 0.087 0 0.000*** 0.968 6 0.000***
2003-2005 30.553 6 0.063 8 0.000*** 0.963 3 0.000***
2006-2008 33.795 9 0.012 0 0.000*** 0.973 7 0.000***
2009-2011 43.135 8 0.044 5 0.000*** 0.973 2 0.000***
2012-2014 49.660 3 0.044 8 0.000*** 0.966 4 0.000***
2015-2017 47.245 5 0.021 7 0.000*** 0.972 9 0.000***
2018-2020 42.229 2 0.015 2 0.000*** 0.974 1 0.000***
Table 3  节点对信任均值以及r2、r3计算结果
时间窗口 节点对动机均值 m ( u i , u ) j ˉ 节点对动机与其边聚集系数的相关性r4 相关显著性p4 节点对动机与节点对所在封闭三元组数目的相关性r5 相关显著性p5
1991-1993 962.989 6 -0.089 5 0.000*** 0.845 6 0.000***
1994-1996 1 416.347 5 -0.223 1 0.000*** 0.863 3 0.000***
1997-1999 2 311.219 9 -0.178 8 0.000*** 0.919 5 0.000***
2000-2002 4 319.432 9 -0.111 6 0.000*** 0.910 7 0.000***
2003-2005 5 385.430 0 -0.130 1 0.000*** 0.904 7 0.000***
2006-2008 7 221.712 7 -0.165 5 0.000*** 0.923 2 0.000***
2009-2011 11 089.014 6 -0.118 2 0.000*** 0.930 5 0.000***
2012-2014 13 611.098 4 -0.116 1 0.000*** 0.923 4 0.000***
2015-2017 17 381.426 2 -0.111 0 0.000*** 0.933 6 0.000***
2018-2020 15 349.763 2 -0.115 8 0.000*** 0.937 1 0.000***
Table 4  节点对动机均值以及r4、r5计算结果
z _ o ( u i , u j )(机会) Coefficient(相关系数) t p
z _ c ( u i , u j ) -0.050 4 -8.32 0.000***
z _ b ( u i , u j ) 0.021 9 5.67 0.000***
z _ e ( u i , u j ) 0.098 4 12.26 0.000***
z _ a ( u i , u j ) -0.239 6 -74.89 0.000***
_cons(常数) -0.000 2 -0.07 0.948
Table 5  机会与邻近中心性、中介中心性、特征向量中心性、平均路径长度的回归
z _ t ( u i , u j )(信任) Coefficient(相关系数) t p
z _ c ( u i , u j ) -0.038 4 -5.21 0.000***
z _ b ( u i , u j ) 0.445 1 94.65 0.000***
z _ e ( u i , u j ) 0.297 2 30.43 0.000***
z _ a ( u i , u j ) 0.225 3 57.85 0.000***
_cons(常数) 0.000 03 0.01 0.995
Table 6  信任与邻近中心性、中介中心性、特征向量中心性、平均路径长度的回归
z _ m ( u i , u j )(动机) Coefficient(相关系数) t p
z _ c ( u i , u j ) 0.027 7 3.68 0.000***
z _ b ( u i , u j ) 0.546 5 113.69 0.000***
z _ e ( u i , u j ) 0.487 8 48.84 0.000***
z _ a ( u i , u j ) 0.267 6 67.21 0.000***
_cons(常数) 0.000 1 0.02 0.998
Table 7  动机与邻近中心性、中介中心性、特征向量中心性、平均路径长度的回归
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