Using Structure Holes for Determining Key Factors: An Illustration of Reporting Eradication of Amoebiasis
Applied and Computational Mathematics
Volume 6, Issue 4-1, July 2017, Pages: 55-63
Received: Dec. 20, 2016; Accepted: Jan. 9, 2017; Published: Jan. 24, 2017
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Tsair-Wei Chien, Research Departments, Chi-Mei Medical Center, Tainan, Taiwan; Department of Hospital and Health Care Administration, Chia-Nan University of Pharmacy and Science, Tainan, Taiwan
Shih-Bin Su, Department of Occupation Medicine, Chi-Mei Medical Center, Tainan, Taiwan
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Background: Many researches aim to determine key factors affecting their concerns of interest using traditional statistical techniques, such as logistical or linear regressions. Social network analysis (SNA) is a newly novel way determining key roles through the use of network and graph theories recently. An example of commonly visualized through SNA is the disease transmission path of Middle East respiratory syndrome (MERS). Purpose: To determine key roles using structure holes of SNA for further improvement, and to show the SNA advantage over traditional classic test theory. Methods: Data were records regarding 443 adult mentally retarded residents who were infected with amoebiasis and distributed in 10 houses in past 10 years. A series of intensive mass screenings and treatment interventions were conducted. Structure holes were applied to verify the efficacy of determining key roles and strong associations for the domains of interest in a network and compared with the result obtained from the traditional Chi-square statistics. Results: The classification of key roles in a network (e.g., with which year the residency room with amoebiasis cases has strongly association) can be effectively discriminated through the structure holes of SNA. Though the result is similar to the traditional Chi-square statistics, the structure holes can release much more useful and valuable information for further investigation. Conclusions: Because of advances in computer technology, the number of healthcare studies for the group classification and association assertion continues to increase and benefit comparisons of data if structure holes of SNA are applied.
Social Network Analysis, Structure Holes, Chi-Square Statistics, Middle East Respiratory Syndrome, Amoebiasis
To cite this article
Tsair-Wei Chien, Shih-Bin Su, Using Structure Holes for Determining Key Factors: An Illustration of Reporting Eradication of Amoebiasis, Applied and Computational Mathematics. Special Issue: Some Novel Algorithms for Global Optimization and Relevant Subjects. Vol. 6, No. 4-1, 2017, pp. 55-63. doi: 10.11648/j.acm.s.2017060401.15
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Friedlander S, Silver M. A quantitative study of the determinants of fertility behavior. Demography. 1967;4 (1): 30-70.
Zhai L, Fu S, Zhang C, Liu Y, Wang L, Liu G, Yang M. An efficient classification method based on principal component and sparse representation. Springerplus. 2016;5 (1): 832.
Su SB, Guo HR, Chuang YC, Chen KT, Lin CY. Eradication of amoebiasis in a large institution for mentally retarded in Taiwan. Infect Control Hosp Epidemiol. 2007;28 (6): 679-83.
Lai WP, Chien TW, Lin HJ, Su SB, Chang CH. A screening tool for dengue fever in children. Pediatr Infect Dis J 2013;32 (4): 320-4.
Cowling BJ, Park M, Fang VJ, Wu P, Leung GM, Wu JT. Preliminary epidemiological assessment of MERS-CoV outbreak in South Korea, May to June 2015. Euro Surveill. 2015;20 (25): 7-13.
Cyram Inc. Data: MERS-CoV. 2016/07/14 retrieved at
Burt RS. Structural Holes: The Social Structure of Competition. Cambridge: Harvard University Press, 1995.
Burt RS. Structural holes and good ideas. American Journal of Sociology 2004;110: 349–399.
Burt RS, Hogarth RM, Michaud C. The social capital of French and American managers. Organization Science 2000;11: 123–147.
Chein. Calculation of structure holes. 2016/07/14 retrieved at
Batagelj V, Mrvar A. Pajek - Analysis and Visualization of Large Networks. in Jünger, M., Mutzel, P., (Eds.) Graph Drawing Software. Springer, Berlin 2003;77-103.
Batagelj V, Mrvar A. Pajek-program for large network analysis. Connections. 1998;21: 47–57.
Borgatti SP, Everett MG, Freeman LC. UCINET 6.0, Version 1.00. Lexington, KY: Analytic Technologies; 1999.
Grunspan DZ, Wiggins BL, Goodreau SM.Understanding Classrooms through Social Network Analysis: A Primer for Social Network Analysis in Education Research. CBE Life Sci Educ. 2014;13 (2): 167–178.
Borgatti SP, Mehra A, Brass DJ, Labianca G. Network analysis in the social sciences. Science. 2009;323: 892–895.
Morris M. Network Epidemiology: A Handbook for Survey Design and Data Collection. Oxford, UK: Oxford University Press; 2004.
Barabási A-L, Gulbahce N, Loscalzo J. Network medicine: a network-based approach to human disease. Nat Rev Genet. 2011;12: 56–68.
Newman ME. The structure of scientific collaboration networks. Proc Natl Acad Sci USA. 2001;98: 404–409.
West JD, Bergstrom TC, Bergstrom CT. The Eigenfactor MetricsTM: a network approach to assessing scholarly journals. Coll Res Libr. 2010;71: 236–244.
Christakis NA, Fowler JH. Social contagion theory: examining dynamic social networks and human behavior. Stat Med. 2013;32: 556–577.
Wang Y, Tan XD, Zhou C, Zhou W, Peng JS, Ren YS, Ni ZL, Liu B, Yang F, Gao XD. Exploratory social network analysis and gene sequencing in people who inject drugs infected with hepatitis C virus. Epidemiol Infect. 2016;13: 1-11.
Lee IC, Ting TT, Chen DR, Tseng FY, Chen WJ, Chen CY. Peers and social network on alcohol drinking through early adolescence in Taiwan. Drug Alcohol Depend. 2015;153: 50-8.
Zare-Farashbandi F, Geraei E, Siamaki S. Study of co-authorship network of papers in the Journal of Research in Medical Sciences using social network analysis. J Res Med Sci. 2014;19(1): 41-6.
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