Family Medicine and Primary Care: Open Access (ISSN: 2688-7460)

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Google Maps to Show International Co-Author Collaborations for the Journal of ‘Family Medicine’ and ‘Primary Care’

Tsair-Wei Chien1,2, Wei-Chih Kan2,3,Hsien-Yi Wang2, Willy Chou4,5*

1Research Department, Chi-Mei Medical Center, Taiwan

2Nephrology Department, Chi-Mei Medical Center, Taiwan

3Department of Biological Science and Technology, Chung Hwa University of Medical Technology, Taiwan

4Department of physical medicine and rehabilitation, Chi Mei medical center, Taiwan

5Department of Recreation and Health-Care Management & Institute of Recreation, Industry Management, Chia Nan University of Pharmacy, Taiwan

*Corresponding author: Willy Chou, Department of physical medicine and rehabilitation,Chi-Mei Medical Center, 901 Chung Hwa Road, Yung Kung Dist., Tainan 710, Taiwan, Tel: +88662812811 Ext: 52000; Email: ufan0101@ms22.hinet.net

Received Date: 28 December, 2018; Accepted Date: 13 February, 2019; Published Date: 20 February, 2019

1.     Abstract

Context: Identifying international coauthor collaborations for journal papers is important and meaningful. However, no any paper that can combine Google map and social network analysis(SNA) to present valuable information for readers.

Aims: Our aims were to visualize and compare the feature of international coauthor collaborations for two prominent journals and present the result on Google maps using SNA.

Settings and Design: Downloading 4764 articles on November 5, 2018 from Pubmed.com, we analyzed author nation and report features: (1) Nations published the most papers in Family Medicine and Primary care; (2) Indicators related to international coauthor collaboration; (3) Graphical representations to report the nation distribution for two journals.

Methods and Materials: Google Maps based on the coordinates of latitude and longitude were used to display results. Pajek software was performed to yield centrality measures in a network.

Statistical analysis used: Descriptive statistics and visual presentations.

Results: We found that the top nation for the two journals is similarly from U.S. accounting for 92.63& and 98.03% for Family Medicine and Primary Care, respectively. The Google maps combined with SNA to demonstrate the most frequency of author nationsisshown the dominant nation from U.S., no any author collaboration with other countries or regions.

Conclusions: Google map combined with SNA provides wide and deep insight into the relationships among nations and coauthor collaborations. The results can be provided to readers for the submission to the journal with the aims and the scope related to Family Medicine and Primary Care.

2.     Keywords: Authorship collaboration; Family medicine; Google map, Primary care; Social network analysis

1.                  Introduction

Family Medicine (FM) is a specialty devoted to comprehensive health care for people of all ages[1].Family physicians are often primary care physicians based on knowledge of the patient in the context of the family and the community[2].The aim of family medicine provides personal, comprehensive, and continuing care for the individual[3]. However, no such information about authors’ collaborationson Family Medicine and Primary Care havebeen reported in literature even if we have found 4,764 papers published in journals of Family Medicine and Primary Care in Pubmed.com library at the end of 2017. A research question is thus conceived on the issue of investigating the feature of author nation collaboration for both journals of Family Medicine and Primary Care.

Social Network Analysis(SNA) [4-6] has been reported to inspect authorship collaboration because co-authorship among researchers that forms a type of social network[5]. The concept of co-occurrence can be investigated[7-9] using SNA.

Our aims are to investigate the international coauthor collaborations for two journals of Family Medicine and Primary Care with following steps: (1) What nation based on the 1st author published the most papers in past years; (2) What indicators that can be used for reporting international coauthor collaboration for journals; (3) How to show results on Google Maps and report the cluster relations among nations.

2.                  Subjects and Methods

2.1.              Data Sources

We downloaded data including author names, author nations, and the publication journals from the PubMed database (Pubmed.org) maintained by the US National Library of Medicine, National Institutes of Health with the keyword of Family Medicine [Journal] and Primary Care [Journal] on November 5, 2017. Microsoft Excel VBA(visual basic for applications) modules were programed by authors to organize data for the use in this study. A total of 4,764journal articles were retrieved. Only 3491 eligible papers that provide nation labels for authorsare used in this study.

2.2                Data Arrangement to Fit SNA Requirement

Beforevisualizing representations of research findings using SNA, we arranged data in compliance with the SNA format and guidelines using Pajek software[10]. Microsoft Excel VBA was applied to make data fitting the SNA requirement. For more information about the data format, see Pajek guideline at http://vlado.fmf.uni-lj.si/pub/networks/pajek/

2.3                Graphical Representations to Report

2.3.1.         The most number of papers published by nations

Many article types are categorizedon Pubmed.com,we merely extracted these papers of a journal article from the library and made tables to presentnations based on the 1st author that published the most in the fields of Family Medicine and Primary Care.

2.3.2.         Author nations and their relations

Google Map is suitable for presenting the author-nation distribution on earth by either nation or cluster with coordinates of latitude and longitude[11]. Visual representations were generated to report the clusters of nations on a Google Map, and show international author collaborations based on the coordinates of latitude and longitude.

2.3.3.         Collaboration indicators between two journals

Centrality is an important index to analyze the network. Any individual or entity lied in the center of the social network will determine its influence on the network and its speed to gain information [12].

Density was defined as the total number of unweighted relational ties(i.e., only once counted for each pair connection) divided by the total possible number of relational ties [13], which was calculated by the equation of degree centrality. The weighted degree indicates more than one times counted for each pair connection.

Collaboration Index(CI) denotes a ratio of author number divided by the number of papers(CI , where fi is the frequency for each category (j, from 1 to k) of author number, N is the number of papers, aj represents the author number in each category(j). The degree of collaboration(DC ) means a ratio of themultiply author.

Gini coefficient[14] was applied to measure the inequality of published papers among the top five clusters(i.e., selecting the most number of published papers from a cluster). If a dominant power or influence exists in a network, the Gini coefficient will be higher near to 1.0.

2.3.4.         Statistical tools and data analyses

SNA Pajek software[10] was used to obtain the measures of centrality. Google map was applied to display visualized representations. Author-made Excel VBA modules were prepared for organizing data and matching nations’ coordinates of latitude and longitude. .

3.                  Results

3.1.              The most number of papers published by nations

The most number of papersare shown in Table 1(n=2021 due to some papers without specific nation labels on authors) and Table 2(n=1472) respectively for Family Medicine and Primary Care on Pubmed.com. We can see that the top nation for the two journals is similarly from U.S. accounting for 92.63& and 98.03% for Family Medicine and Primary Care, respectively.

3.2.              Author nations and their relations

Authors’ nation clusters are distributed in Figure 1 and Figure 2for Family Medicine and Primary Care, respectively[15,16]. We can see that the two nations of U.S. and Canada have the dominant power and influence on both journals because they published many papers on the two journals. Each nationis colored by the publications.

3.3.              Comparison of collaboration indicators between two journals

We can see both journals have dominant power and influence (i.e., Gini coefficient>0.97, see Table 3) from the U.S. on the issue of family medicine and primary care. No any author collaboration with other countries or regions was found. The Journal of Family Medicine has more nations(42) than the counterpart of the Journal of Primary Care(11). However, the Primary Care has two coauthors from other countries(i.e. Canada and Peru) in conjunction with the U.S. All papers published in Family Medicine were sole-nation-type articles. The Journal of Primary Care has an earlier publication since 1974 than the Journal of Family Medicine since 1985.

Note. 

6.                  Discussion

The top nation for the two journals is similarly from U.S. accounting for 92.63& and 98.03% for Family Medicine and Primary Care, respectively. The Google maps combined is shown the dominant nation from the U.S., no any author collaboration with other countries or regions.The Journal of Family Medicine has more nations (42) than the counterpart of the Journal of Primary Care(11).

7.                  What This Adds to What Was Known

This study combined Google map with SNA to demonstrate that the most frequency of authors is from the U.S., indicating that one picture is worth one thousand wordswhen Google map can provide more valuable information to readers.

No, any paper has used Google Maps to show international coauthor collaborations in a dynamicallyeffective form. In data analysis, it is very hard to detect the association of two or more entities at one time. We applied SNA to explore the relation of any two nations of their coauthors that can be shownthe closest collaboration in a paper publication. Hyperlinks at references [15,16] are provided to interested readers who can manipulate the Google Maps with the functionalities of zoom-in and zoom-out to know the details of information such as network density of centrality and Gini coefficient can be shown.

8.                  What it Implies and what should be Changed?

Papers downloaded from Pubmed.comwere implemented,and a total of 4764 articles were extracted and studied. If no such Excel modules[17,18] were used, it is impossible to yield a visual presentation[15,16] used for interpreting the results of the study aboutthe international coauthor collaboration in literature.

Many previous types of research [4-6] have investigated coauthor collaboration using SNA. However, we have not seen any that can demonstrate a concrete way to show how to conduct this exploration of informative messages to readers. We showed how easy and possible the SNA could display all possible pairs of our observed phenomena in a short time incorporating the free-charged Pajek software with Google Maps. Journal authorship collaboration can be thus compared with each other, see Figure 1 and Figure 2. We can see that the author-nation-pattern was the prevailing one which is similar to the previous study[4].

9.                  Strengths of this Study

International collaboration in science has increased rapidly in recent decades. One driver of this development has been the efforts of the European Commission to stimulate collaboration within the European Union across sectors and nations [19]. The development also self-organizes at the global level of the United States and other advanced industrial nations for reasons driven by the demands of science. Mass data storage of electronic communications [20] with less expensive travel may also contribute the drivers and facilitators to the author collaboration in science [21]. Some governments [22] even invest purposefully in the stimulation of “internationalization” in science to promote the international coauthor collaborations more than ever before. However, we have not seen any international collaboration in the two journals of Family Medicine and Primary Care.

Since the advent of bibliometrics, citation analysis has been widely used in many disciplines to evaluate the influence of academic articles [23-31]. It is worth using SNA, especially incorporating with Google map, to report journal or topic features in the future.

10.              Limitations and Future Study

There are some limitations to this study. Interpretation and generalization of the conclusions of this study should be carried out with caution. First, the data of this study were collected from Pubmed.com. It is worth noting that any attempt to generalize the findings of this study should be made in similardisciplines anddomains with similar topic and the scope.

Second, although the data were extracted from Pubmed.com and carefully dealt with every linkage as correct as possible, the original downloaded text file including some errors in the name ofthe nation because some were not well recordedin the context of the downloaded data such as author’s nation that might lead to some bias in the results. Third, there are many algorithms used for SNA. We merely applied centrality measure to present the prestigious feature.

Any changes made along with algorithm used will present different pattern and judgment. Fourth, the social network analysis is not subject to the Pajeck software we used in this study, Others such as Ucinet[32] and Gephi[33] are suggested to readers for use in future.

11.              Conclusion

Social network analysis provides wide and deep insight into the relationships among nations, and coauthor collaborations related to the keyword of physiotherapy. The results can be providedto readers for the submission to the journal with the aims and the scope related to physiotherapy.


Figure 1: Cluster distribution for nations of 1st author using Pajak coordinatesfrom the Journal of Family Medicine.



Figure 2: Cluster distribution for nations of 1st author using Google coordinates for the Journal of Primary Care.

No.

Nation

<-2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

Total

%

1

U.S.

1225

75

62

65

66

77

73

57

44

44

47

37

1872

92.63

2

Canada

34

1

5

2

1

43

2.13

3

Netherlands

10

1

1

1

13

0.64

4

Lebanon

4

1

1

1

1

1

1

10

0.49

5

Israel

7

1

8

0.40

6

Brazil

3

2

1

6

0.30

7

Norway

5

1

6

0.30

8

Germany

1

2

1

1

5

0.25

9

Japan

2

1

1

1

5

0.25

10

New Zealand

2

1

1

4

0.20

11

U.K.

0

2

1

1

4

0.20

12

Australia

1

2

3

0.15

Others

19

3

0

2

5

2

2

2

3

0

2

2

42

2.08

Total

1313

83

65

75

76

82

79

60

49

47

52

40

2021

100.00


Table 1: Top 12 nations whose papers from the Journal of Family Medicine across years based on 1st author’s nation.


Nation

<-2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

Total

%

U.S.

941

38

42

47

47

42

45

50

50

46

52

43

1443

98.03

Canada

11

2

1

1

15

1.02

U.K.

3

1

4

0.27

Australia

3

3

0.20

Finland

1

1

0.07

Ireland

1

1

0.07

Netherlands

1

1

0.07

Philippines

0

1

1

0.07

Portugal

0

1

1

0.07

Ukraine

1

1

0.07

Venezuela

1

1

0.07

Total

963

40

43

47

47

44

46

51

50

46

52

43

1472

100.00


Table 2: Top 11 nations whose papers from the Journal of Primary Care across years based on 1st author’s nation.


Number

1 nation

2  nations

3  nations

4 nations

>=5 nations

Total

Journal

Count

%

Count

%

Count

%

Count

%

Count

%

Count

CI

Family Medicine

2021

100.00

0

0

0

0

0

0

0

0

2021

1.00

Primary Care

1470

99.86

2

0.14

0

0.00

0

0.00

0

0.00

1472

1.00

Total

3491

99.94

2

0.06

0

0.00

0

0.00

0

0.00

3493

1.00

Journal

Eligible

papers

Nations

1st author

Nations

Participated

Ratio

(%)

Gini

Coeff.

DC

%

Paper

downloaded

Max.

connection

Mean of

degree

Degree

density

Weighted

density

End at

2017

Family Medicine

2021

42

42

100

0.97

0.00

2731

0

0.00

0.00%

0.00%

1985

Primary Care

1472

11

12

92

0.99

0.14

2033

2

0.18

3.03%

3.03%

1974

Total

3493

53

54

98

-

-

4764

2

0.04

0.15%

0.15%


Table 3: Comparisons of two journals in some indicators of nation collaboration.

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