structural hole
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2021 ◽  
Vol 6 (2) ◽  
pp. 312-323
Author(s):  
Agus Surya Bakti ◽  
Hafied Cangara ◽  
Dwia Aries Tina Palubuhu ◽  
Eriyanto Eriyanto

The ISIS terrorist group still poses a serious threat in Indonesia, especially because it operates in a network (net-terrorism) so that the handling of this terrorist group often does not reach its roots. The research is aimed to reveal the social network strategy in resolving terrorist acts in Indonesia using a structural hole theory. The research method is a qualitative research approach with secondary data analysis from four sources: books, journal articles, previous related research, and the Law of the Republic of Indonesia. The data above is then processed with Ucinet-Draw to calculate the linkage score between members in the network and then see the movement map for each ISIS network in Indonesia: Jakarta, Poso, and Surabaya. Thus, this study proves that there is a gap in the structure of the ISIS group's communication network in Indonesia. The research results revealed that many terrorist acts in Indonesia had the same pattern, namely the strong communication network between terrorist actors. Terrorist actors carried out at least three tertius strategies, namely tertius gaudens, tertius inguens, and a combination of the two. Through the tertius strategy, the government will be able to play its most crucial role in taking preventive actions against actors in terrorist networks. Therefore, the government needed to carry out various integration strategies with various institutions to conduct deradicalization appropriately.


2021 ◽  
Author(s):  
Yuan Jiang ◽  
Song-Qing Yang ◽  
Yu-Wei Yan ◽  
Tian-Chi Tong ◽  
Ji-Yang Dai

Abstract How to identify influential nodes in complex networks is an essential issue in the study of network characteristics. A number of methods have been proposed to address this problem, but most of them focus on only one aspect. Based on the gravity model, a novel method is proposed for identifying influential nodes in terms of the local topology and the global location. This method comprehensively examines the structural hole characteristics and K-shell centrality of nodes, replaces the shortest distance with a probabilistically motivated effective distance, and fully considers the influence of nodes and their neighbors from the aspect of gravity. On eight real-world networks from different fields, the monotonicity index, susceptible-infected-recovered (SIR) model, and Kendall's tau coefficient are used as evaluation criteria to evaluate the performance of the proposed method compared with several existing methods. The experimental results show that the proposed method is more efficient and accurate in identifying the influence of nodes and can significantly discriminate the influence of different nodes.


2021 ◽  
Author(s):  
Diksha Goel ◽  
Hong Shen ◽  
Hui Tian ◽  
Mingyu Guo

2021 ◽  
Vol 22 (5) ◽  
pp. 1009-1017
Author(s):  
Chinenye Ezeh Chinenye Ezeh ◽  
Tao Ren Chinenye Ezeh ◽  
Yan-Jie Xu Tao Ren ◽  
Shi-Xiang Sun Yan-Jie Xu ◽  
Zhe Li Shi-Xiang Sun


2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Mingxing Li ◽  
Mengjuan Zhang ◽  
Fredrick Oteng Agyeman ◽  
Hira Salah ud din Khan

The automobile industry serves as the primary industry for national development and also enhances manufacturing development strategies. Its source of power comes from the maturity and operational efficiency of the technology innovation network within the industry. Firstly, this paper takes the automobile industry of the Yangtze River Economic Belt as the research object and depicts the topological structure of the 1985–2015 Industry-University-Research Cooperation Innovation Network (IURCIN) from the perspective of space-time evolution. Then, based on the 2015 industrial network characteristic data, the paper analyses the impact of individual network characteristics such as intermediate centrality, structural hole limitation, and cooperation intensity on the innovation performance of the respective network. At the same time, it adds innovation activity, per capita gross regional product (GRP), and research and development (R&D) fund input intensity as control variables in the quantitative analysis. The results show that the centrality and structural hole limitation significantly and positively affect the subject innovation performance. The cooperation intensity and the subject innovation performance have an inverted U-shaped relationship. The innovation activity has a positive effect on the subject’s innovation performance. Furthermore, per capita GRP and R&D expenditure intensity on the main innovation performance is not significant. Finally, the countermeasures and suggestions are put forward to promote the innovation performance of each subject in the IURCIN.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Guan Feiyang ◽  
Wang Tienan ◽  
Sun Linbing ◽  
Tang Liqing

PurposeThe authors selected global automobile manufacturing firms whose sales ranked within 100 in the five years from 2014 to 2018 in the Factiva database to examine how the characteristics of a firm's whole network and ego-network in a transnational coopetition network influence network performance.Design/methodology/approachThe authors analyzed the public news of the sample firms about the coopetition by structural content analysis to build the coopetition networks and access to data on the competitive actions of firms. Then, to measure the variables associated with the coopetition network, such as the structural hole, centrality and ego-network stability, the authors use UCINET 6 that is a widely used piece of software for social network analysis to establishing five undirected binary adjacency matrices.FindingsThe authors find that a firm's competitive aggressiveness mediates the relationship between a firm's whole network position and network performance that emphasizes the need for integrating competitive dynamics research and coopetition research and shows how valuable insights can be gained through such integration. And the interaction of structural hole and centrality impacts competitive aggressiveness and network performance, and the interaction is different under high and low ego-network stability. The integration of whole network and ego-network literature studies provides new insights into firm network literature.Practical implicationsIn the process of cooperation, firms should consider whether they can occupy the structural hole and center as important indicators for partner selection. Too stable relationship will prevent firms from obtaining new resources. Firms should weigh the period of cooperation according to specific situation.Originality/valueThese results indicate that ego-network stability, as an important complementary characteristic of coopetition network, has a significant synergistic effect with structural holes and centrality on competitive aggressiveness and network performance. And these findings expand the current literature on the relationship between characteristics of network, competitive aggressiveness and network performance.


2021 ◽  
Vol 17 (2) ◽  
pp. 155014772199928
Author(s):  
Yongshan Liu ◽  
Jianjun Wang ◽  
Haitao He ◽  
Guoyan Huang ◽  
Weibo Shi

An important node identification algorithm based on an improved structural hole and K-shell decomposition algorithm is proposed to identify important nodes that affect security in complex networks. We consider the global structure of a network and propose a network security evaluation index of important nodes that is free of prior knowledge of network organization based on the degree of nodes and nearest neighborhood information. A node information control ability index is proposed according to the structural hole characteristics of nodes. An algorithm ranks the importance of nodes based on the above two indices and the nodes’ local propagation ability. The influence of nodes on network security and their own propagation ability are analyzed by experiments through the evaluation indices of network efficiency, network maximum connectivity coefficient, and Kendall coefficient. Experimental results show that the proposed algorithm can improve the accuracy of important node identification; this analysis has applications in monitoring network security.


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