Investigating Iranian Information Gatekeepers in the Field of Medical Genetics Using Network Structure Analysis
Journal of Medical Library and Information Science,
Vol. 1 (2020),
1 July 2020
,
Page 1-9
https://doi.org/10.22037/jmlis.v1i.32491
Abstract
Introduction: In the flow of information and scientific communication, two formal and informal relationships are measured through co-authorship. The present study aims to discover the gatekeeper nodes in both types of scientific communication and seek to strengthen the health cycle of medical genetics information.
Methods: This research is applied in terms of purpose, and in terms of nature and method, it is a kind of mixed research, including survey method, scientometrics, and interview and social network analysis. The research population was the researchers in the field of medical genetics in seven selected centers. First, using centrality indicators, gatekeepers were discovered in the formal communication structure. Then, interviewing formal gatekeepers, the gatekeeper's agents were identified in informal communication. The effectiveness of each gatekeeping factors in the informal scientific communication process was determined using the questionnaire.
Results: The network size represents an average degree of 122. Opinion leaders were extracted based on centrality indicators. By interviewing with leaders, 15 units were identified as target nodes in the centers. Among them, the educational deputy had the most positive effect, and the ethics committee had the least positive effect on the research process.
Conclusion: The low amount of degree indicators revealed that the medical genetic communication network is not efficient. Accordingly, most of the negative, informal communication issues are human communication factors such as professors' characteristics. In the research process, some institutions, such as the Ethics Committee, are an inhibitor of communication.
- Social network analysis, Gatekeeping, Information gatekeepers, Medical genetics
How to Cite
References
Lu Y. The human in human information aquisition: undrestanding gatekeeping and proposing new directions in scholarship. Libr Inf Sci Res. 2007;29:103–123. doi: 10.1016/j.lisr.2006.10.007
Lewin K. Group Decision and social change. In: Readings in social psychology [book on the Internet]. New York: Holt, Rinehart & Winston; p. 197–211 [cited 2020 Mar 6]. Available from: http://www.sietmanagement.fr/wp-content/uploads/2016/04/Lewin.pdf
Freeman LC. The gatekeeper, pair-dependency and structural centrality. Qual Quant. 1980;14: 585–592. doi: 10.1007/BF00184720
Barzilai-Nahon K. Toward a theory of network gatekeeping: a framework for exploring information control. J Am Soc Inf Sci Thechnology. 2008;59(9):1493–512. doi: https://doi.org/10.1002/asi.20857
Erzikova E. gatekeeping. In: Heath RL, Johansen W. The international encyclopedia of strategic communication.. Hoboken, NJ: Wiley-Blackwell; 2018. doi: 10.1002/9781119010722.iesc0080
MCginty S. Gatekeepers of knowledges: Journal Editors in the Sciences and the Social Sciences. Westports, CT: Bergin & Garvey. 1999. doi:10.5860/lrts.44n4.217
Sattarzadeh A, Galyani Moghaddam G, Momeni E. The Analysis of the structure of scientific collaboration networks in basic medical sciences in the Science Citation Index from 1996 to 2013. J Sci Stud. 2019;2(6). doi: 10.22054/jks.2016.2707
Soheili F, Sohrabi MG, Atashpaykar S. Co-authorship network analysis of Iranian medical science researchers: A social network analysis. Casp J Sci. 2015;2(1):24–32. doi: 10.22088/acadpub.BUMS.2.1.24. [In Persian].
Mohammadian S, Vaziri E. Analysis and visualisation of scientific collaboration of Iran universities of medical sciences using social network analysis metrics based on web of sciences. Payavard Salamat. 2017;11(1):43-56. [In Persian].
González-Alcaide G, Park J, Huamaní C, Belinchón I RJ. Evolution of cooperation patterns in psoriasis research: co- authorship network analysis of papers in Medline (1942–2013). PLoS One. 2015;10(12): e0144837. doi:10.1371/journal.pone.0144837
Chien TW, Chang Y, Chow JC CW. Using Visual Representations to Present the Pattern of International Co-Author Collaboration in the Field of Molecular and Genetic Research. J Mol Genet Med. 2018;12(1). doi: 10.4172/1747-0862.1000319
Zarei M, Salari M, Jafarzadeh Z. Extracting structural holes in Iran medical genetics scientists’ co-authorship network: a case study of faculty members in five selected centers. Hormozgan Med J. 2018;22 (3): e86617. doi: 10.5812/hmj.86617
Habiba Yu, Yintao BW, Tanya Y SJ. Finding spread blockers in dynamic networks. In: Giles L, Smith M, Yen J, Zhang H (eds) Advances in Social Network Mining and Analysis. SNAKDD 2008. Lecture Notes in Computer Science, vol 5498. Springer, Berlin, Heidelberg. doi: 10.1007/978-3-642-14929-0_4
Erfanmanesh MA, Basirian Jahrom R. The co-authorship network of the articles published in the National Studies on Librarianship and Information Organization Journal using social networks analysis indexes. Q Natl Stud Libr Inf Organ. 2014;24(2): 76-96. [In Persian].
Rogers M. Evolution: Diffusion of innovations. In: Wrighy JD (ed). International Encyclopedia of the Social & Behavioral Sciences. London: Pergamon. 2001[cited 2006 Nov 20]. p. 4982-4986. doi: 10.1016/B978-0-08-097086-8.81064-8
Daland H, Hidle KMW. New roles for research librarians: meeting the expectations for research support [book on the Internet]. Chandos Publishing; 2016. Available from: https://www.elsevier.com/books/new-roles-for-research-librarians/daland/978-0-08-100566-8
Faggion C. Improving the peer-review process from the perspective of an author and reviewer. Br Dent J. 2016;220: 167-168. doi: 10.1038/sj.bdj.2016.131
Björk B-C. Scientific communication life-cycle model. Learn Publ. 2005;18(3): 165–176. doi: 10.1087/0953151054636129
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