Upload data from WoS and Scopus databases.
library(bibliometrix)## To cite bibliometrix in publications, please use:
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## Aria, M. & Cuccurullo, C. (2017) bibliometrix: An R-tool for comprehensive science mapping analysis,
## Journal of Informetrics, 11(4), pp 959-975, Elsevier.
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## https://www.bibliometrix.org
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##
## For information and bug reports:
## - Send an email to info@bibliometrix.org
## - Write a post on https://github.com/massimoaria/bibliometrix/issues
##
## Help us to keep Bibliometrix free to download and use by contributing with a small donation to support our research team (https://bibliometrix.org/donate.html)
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## To start with the shiny web-interface, please digit:
## biblioshiny()library(xlsx)
wos_data1985to2020 <- convert2df("/Users/julietarodriguez/Downloads/savedrecs-1985to2020.txt", dbsource = "wos", format="plaintext")##
## Converting your wos collection into a bibliographic dataframe
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## Done!
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## Generating affiliation field tag AU_UN from C1: Done!wos_data2021 <- convert2df("/Users/julietarodriguez/Downloads/savedrecs-2021.txt", dbsource = "wos", format="plaintext")##
## Converting your wos collection into a bibliographic dataframe
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## Done!
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## Generating affiliation field tag AU_UN from C1: Done!scopus_data1975to2019 <- convert2df("/Users/julietarodriguez/Downloads/scopus-1975to2016.bib", dbsource = "scopus", format = "bibtex")##
## Converting your scopus collection into a bibliographic dataframe
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## Done!
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## Generating affiliation field tag AU_UN from C1: Done!scopus_data2020to2021 <- convert2df("/Users/julietarodriguez/Downloads/scopus-2017to2020.bib", dbsource = "scopus", format = "bibtex")##
## Converting your scopus collection into a bibliographic dataframe
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## Done!
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## Generating affiliation field tag AU_UN from C1: Done!Merge data and remove duplicates:
fulldata <- mergeDbSources(wos_data1985to2020, wos_data2021, scopus_data1975to2019, scopus_data2020to2021, remove.duplicated = T)##
## 620 duplicated documents have been removedresults <- biblioAnalysis(fulldata)
summary(results, k=10, pause=F, width=130)##
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## MAIN INFORMATION ABOUT DATA
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## Timespan 1975 : 2022
## Sources (Journals, Books, etc) 1339
## Documents 3145
## Annual Growth Rate % 8.83
## Document Average Age 4.82
## Average citations per doc 16.7
## Average citations per year per doc 3.198
## References 130535
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## DOCUMENT TYPES
## article 1706
## article; book chapter 7
## article; early access 8
## article; proceedings paper 8
## book 15
## book chapter 54
## book review 1
## conference paper 642
## conference review 27
## correction 3
## data paper 1
## editorial 84
## editorial material 45
## editorial material; book chapter 1
## erratum 9
## letter 43
## meeting abstract 36
## note 74
## reprint 1
## review 370
## short survey 9
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## DOCUMENT CONTENTS
## Keywords Plus (ID) 12625
## Author's Keywords (DE) 6031
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## AUTHORS
## Authors 11019
## Author Appearances 15822
## Authors of single-authored docs 335
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## AUTHORS COLLABORATION
## Single-authored docs 408
## Documents per Author 0.285
## Co-Authors per Doc 5.03
## International co-authorships % 11.35
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## Annual Scientific Production
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## Year Articles
## 1975 1
## 1978 1
## 1981 1
## 1982 2
## 1984 7
## 1985 3
## 1986 7
## 1987 14
## 1988 2
## 1989 6
## 1990 4
## 1991 2
## 1992 5
## 1993 6
## 1994 6
## 1995 3
## 1996 2
## 1997 4
## 1998 5
## 1999 2
## 2000 3
## 2001 8
## 2002 8
## 2003 8
## 2004 7
## 2005 11
## 2006 17
## 2007 17
## 2008 19
## 2009 28
## 2010 25
## 2011 34
## 2012 59
## 2013 67
## 2014 94
## 2015 101
## 2016 144
## 2017 222
## 2018 335
## 2019 550
## 2020 875
## 2021 387
## 2022 35
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## Annual Percentage Growth Rate 7.858037
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## Most Productive Authors
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## Authors Articles Authors Articles Fractionalized
## 1 NA N 41 NA N 41.00
## 2 ZHANG Y 39 KIM J 7.06
## 3 WANG Y 30 ZHANG Y 6.75
## 4 LI J 23 BICHINDARITZ I 5.83
## 5 KIM J 22 OHAYON M 5.50
## 6 KESSLER R 20 WANG Y 5.40
## 7 WANG J 20 KIM Y 5.18
## 8 KOUTSOULERIS N 19 LUXTON D 4.58
## 9 VENKATESH S 19 VENKATESH S 4.43
## 10 WANG X 19 ZHANG T 4.34
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## Top manuscripts per citations
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## Paper DOI TC TCperYear NTC
## 1 PENNEBAKER JW, 2003, ANNU REV PSYCHOL 10.1146/annurev.psych.54.101601.145041 1445 72.2 7.80
## 2 LIU S, 2020, LANCET PSYCHIATRY 10.1016/S2215-0366(20)30077-8 957 319.0 91.58
## 3 DE CHOUDHURY M, 2013, INT CONF WEBLOGS SOC MEDIA, ICWSM NA 824 82.4 21.79
## 4 LI SJ, 2020, INT J ENV RES PUB HE 10.3390/ijerph17062032 673 224.3 64.40
## 5 ORRÙ G, 2012, NEUROSCI BIOBEHAV REV 10.1016/j.neubiorev.2012.01.004 672 61.1 19.28
## 6 HUYS QJM, 2016, NAT NEUROSCI 10.1038/nn.4238 375 53.6 13.18
## 7 ZEMAN A, 2001, BRAIN 10.1093/brain/124.7.1263 371 16.9 4.33
## 8 MÜLLER KR, 2008, J NEUROSCI METHODS 10.1016/j.jneumeth.2007.09.022 332 22.1 9.49
## 9 BURNS MN, 2011, J MED INTERNET RES 10.2196/jmir.1838 331 27.6 9.07
## 10 TOROUS J, 2020, JMIR MENT HEAL 10.2196/18848 320 106.7 30.62
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## Corresponding Author's Countries
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## Country Articles Freq SCP MCP MCP_Ratio
## 1 USA 767 0.3185 690 77 0.1004
## 2 CHINA 214 0.0889 182 32 0.1495
## 3 UNITED KINGDOM 186 0.0772 146 40 0.2151
## 4 AUSTRALIA 148 0.0615 125 23 0.1554
## 5 GERMANY 131 0.0544 106 25 0.1908
## 6 CANADA 107 0.0444 91 16 0.1495
## 7 KOREA 78 0.0324 72 6 0.0769
## 8 FRANCE 73 0.0303 59 14 0.1918
## 9 INDIA 72 0.0299 69 3 0.0417
## 10 NETHERLANDS 70 0.0291 56 14 0.2000
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## SCP: Single Country Publications
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## MCP: Multiple Country Publications
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## Total Citations per Country
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## Country Total Citations Average Article Citations
## 1 USA 17827 23.243
## 2 UNITED KINGDOM 4756 25.570
## 3 GERMANY 3627 27.687
## 4 CHINA 3277 15.313
## 5 AUSTRALIA 2188 14.784
## 6 CANADA 1807 16.888
## 7 SWITZERLAND 1151 25.022
## 8 KOREA 946 12.128
## 9 NETHERLANDS 941 13.443
## 10 ITALY 926 18.157
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## Most Relevant Sources
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## Sources
## 1 LECTURE NOTES IN COMPUTER SCIENCE (INCLUDING SUBSERIES LECTURE NOTES IN ARTIFICIAL INTELLIGENCE AND LECTURE NOTES IN BIOINFORMATICS)
## 2 FRONTIERS IN PSYCHIATRY
## 3 JOURNAL OF MEDICAL INTERNET RESEARCH
## 4 PLOS ONE
## 5 JMIR MENTAL HEALTH
## 6 BIOLOGICAL PSYCHIATRY
## 7 INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
## 8 TRANSLATIONAL PSYCHIATRY
## 9 JAMA PSYCHIATRY
## 10 JOURNAL OF AFFECTIVE DISORDERS
## Articles
## 1 98
## 2 58
## 3 56
## 4 36
## 5 34
## 6 30
## 7 28
## 8 28
## 9 27
## 10 27
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## Most Relevant Keywords
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## Author Keywords (DE) Articles Keywords-Plus (ID) Articles
## 1 MACHINE LEARNING 767 HUMAN 1167
## 2 MENTAL HEALTH 391 MACHINE LEARNING 946
## 3 ARTIFICIAL INTELLIGENCE 256 HUMANS 827
## 4 DEPRESSION 206 MENTAL HEALTH 700
## 5 DATA MINING 140 ARTIFICIAL INTELLIGENCE 674
## 6 PSYCHIATRY 111 ARTICLE 653
## 7 SCHIZOPHRENIA 111 FEMALE 653
## 8 NATURAL LANGUAGE PROCESSING 105 MALE 653
## 9 SOCIAL MEDIA 100 MENTAL DISEASE 610
## 10 DEEP LEARNING 79 ADULT 538