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Endocrine, Metabolic & Immune Disorders - Drug Targets

Author(s): Mahdiyeh Khazaneha, Farideh Osareh* and Kaveh Shafiee

DOI: 10.2174/1871530320666200607194810

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Trend Linking of Multiple System Atrophy: A Scientometric Study

Page: [700 - 710] Pages: 11

  • * (Excluding Mailing and Handling)

Abstract

Aim: This study aims to add to previous analyses and describe the trends in MSA research from three decades, 1988 to 2018, through assessing the medical literature. Additionally, a collaboration network was analyzed to determine the most common process in development of MSA research.

Methods: This research was a descriptive survey with a scientometric approach. The data for the present study were collected from the Web of Science (WoS) and search strategy based on Medical Subject Heading (MeSH) term. In this research, the data analysis was performed based on collaboration network and theme analysis.

Results and Conclusion: In this study, 6530 articles were retrieved from 1988 to 2018 divided in three different periods. These articles were drafted by 39,184 authors, 3,865 organizations, 80 countries, and 832 journals. Further, 287 articles with more than 100 citations were found. The global citation score (GCS) was 250,834 times and the average citations per article was 3,841 times. The MSA research field demonstrated a diagram for a chronological period to assess the most relevant themes. Each diagram depended on the sum of documents linked to each research topic. Scientometric analysis of the field of MSA can be regarded as a roadmap for future research and policymaking in this important area.

Keywords: Multiple system atrophy, research, scientometric, theme, trend, articles.

Graphical Abstract

[1]
Jecmenica-Lukic, M.; Poewe, W.; Tolosa, E.; Wenning, G.K. Premotor signs and symptoms of multiple system atrophy. Lancet Neurol., 2012, 11(4), 361-368.
[http://dx.doi.org/10.1016/S1474-4422(12)70022-4] [PMID: 22441197]
[2]
Hayes, M.T. Parkinson’s disease and parkinsonism. Am. J. Med., 2019, 132(7), 802-807.
[http://dx.doi.org/10.1016/j.amjmed.2019.03.001] [PMID: 30890425]
[3]
Garfield, E.; Merton, R.K. Citation indexing: Its theory and application in science, technology, and humanities; Wiley New York, 1979, Vol. 8, .
[4]
Bornmann, L.; Haunschild, R.; Hug, S.E. Visualizing the context of citations referencing papers published by Eugene Garfield: a new type of keyword co-occurrence analysis. Scientometrics, 2018, 114(2), 427-437.
[http://dx.doi.org/10.1007/s11192-017-2591-8] [PMID: 29449748]
[5]
Hess, D. J. Science studies: An advanced introduction; NYU press, 1997.
[6]
Van den Besselaar, P.; Heimeriks, G. Mapping research topics using word-reference co-occurrences: a method and an exploratory case study. Scientometrics, 2006, 68(3), 377-393.
[http://dx.doi.org/10.1007/s11192-006-0118-9]
[7]
Osareh, F. Bibliometrics, citation analysis and co-citation analysis: a review of literature I. Libri, 1996, 46(3), 149-158.
[http://dx.doi.org/10.1515/libr.1996.46.3.149]
[8]
Liu, Z.; Lu, Y.; Peh, L.C. A review and scientometric analysis of global 2 Building Information Modelling (BIM) research in 3 the Architecture, Engineering and Construction 4 (AEC) industry 5.,2019.
[9]
Waltman, L.; Van Eck, N.J.; Noyons, E.C. A unified approach to mapping and clustering of bibliometric networks. J. Informetrics, 2010, 4(4), 629-635.
[http://dx.doi.org/10.1016/j.joi.2010.07.002]
[10]
Card, M. Readings in information visualization: using vision to think; Morgan Kaufmann, 1999.
[11]
Cobo, M.J. SciMAT: A new science mapping analysis software tool. J. Am. Soc. Inf. Sci. Technol., 2012, 63(8), 1609-1630.
[http://dx.doi.org/10.1002/asi.22688]
[12]
van Eck, N.J.; Waltman, L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 2010, 84(2), 523-538.
[http://dx.doi.org/10.1007/s11192-009-0146-3] [PMID: 20585380]
[13]
Chen, C. Science mapping: a systematic review of the literature. J. Data Info. Sci., 2017, 2(2), 1-40.
[http://dx.doi.org/10.1515/jdis-2017-0006]
[14]
Chen, S. Exploring the interdisciplinary evolution of a discipline: the case of Biochemistry and Molecular Biology. Scientometrics, 2015, 102(2), 1307-1323.
[http://dx.doi.org/10.1007/s11192-014-1457-6]
[15]
Rafols, I.; Porter, A.L.; Leydesdorff, L. Science overlay maps: a new tool for research policy and library management. J. Am. Soc. Inf. Sci. Technol., 2010, 61(9), 1871-1887.
[http://dx.doi.org/10.1002/asi.21368]
[16]
Leydesdorff, L.; Goldstone, R.L. Interdisciplinarity at the journal and specialty level: the changing knowledge bases of the journal cognitive science. J. Assoc. Inf. Sci. Technol., 2014, 65(1), 164-177.
[http://dx.doi.org/10.1002/asi.22953]
[17]
Leydesdorff, L.; Rafols, I. A global map of science based on the ISI subject categories. J. Am. Soc. Inf. Sci. Technol., 2009, 60(2), 348-362.
[http://dx.doi.org/10.1002/asi.20967]
[18]
Wagner, C.S.; Brahmakulam, I.; Jackson, B.; Wong, A.; Yoda, T. Science and technology collaboration: Building capability in developing countries; RAND Corp.: Santa Monica, CA, 2001.
[19]
Melin, G. Pragmatism and self-organization: research collaboration on the individual level. Res. Policy, 2000, 29(1), 31-40.
[http://dx.doi.org/10.1016/S0048-7333(99)00031-1]
[20]
Sonnenwald, D.H. Scientific collaboration. Annu. Rev. Inform. Sci. Tech., 2007, 41(1), 643-681.
[http://dx.doi.org/10.1002/aris.2007.1440410121]
[21]
Wagner, C.S. Science and technology collaboration: Building capability in developing countries; RAND Corp.: Santa Monica, CA, 2001.
[22]
Glänzel, W.; Schubert, A. Analysing scientific networks through co-authorship.Handbook of quantitative science and technology research; Springer, 2004, pp. 257-276.
[23]
Melin, G.; Persson, O. Studying research collaboration using co-authorships. Scientometrics, 1996, 36(3), 363-377.
[http://dx.doi.org/10.1007/BF02129600]
[24]
Liao, H. A bibliometric analysis and visualization of medical big data research. Sustainability, 2018, 10(1), 166.
[http://dx.doi.org/10.3390/su10010166]
[25]
Nafade, V.; Nash, M.; Huddart, S.; Pande, T.; Gebreselassie, N.; Lienhardt, C.; Pai, M. A bibliometric analysis of tuberculosis research, 2007-2016. PLoS One, 2018, 13(6)e0199706
[http://dx.doi.org/10.1371/journal.pone.0199706] [PMID: 29940004]