Robert Z. Selden, Jr. 20 May, 2021
The dataset used in this analysis was harvested from
Scopus, includes all
articles published in Kiva from 2001 - 2020, and was analysed using
the bibliometrix package (Aria and Cuccurullo 2017).
# install bibliometrix and load data
# devtools::install_github("massimoaria/bibliometrix")
# load
library(here)## here() starts at D:/github/kivabib
library(bibliometrix)## To cite bibliometrix in publications, please use:
##
## Aria, M. & Cuccurullo, C. (2017) bibliometrix: An R-tool for comprehensive science mapping analysis,
## Journal of Informetrics, 11(4), pp 959-975, Elsevier.
##
##
## https://www.bibliometrix.org
##
##
## For information and bug reports:
## - Send an email to [email protected]
## - 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)
##
##
## To start with the shiny web-interface, please digit:
## biblioshiny()
library(reshape2)
library(ggplot2)
# data frame
df <- convert2df(file = "scopus.bib",
dbsource = "scopus",
format = "bibtex")##
## Converting your scopus collection into a bibliographic dataframe
##
##
## Warning:
## In your file, some mandatory metadata are missing. Bibliometrix functions may not work properly!
##
## Please, take a look at the vignettes:
## - 'Data Importing and Converting' (https://www.bibliometrix.org/vignettes/Data-Importing-and-Converting.html)
## - 'A brief introduction to bibliometrix' (https://www.bibliometrix.org/vignettes/Introduction_to_bibliometrix.html)
##
##
## Missing fields: ID
## Done!
##
##
## Generating affiliation field tag AU_UN from C1: Done!
results <- biblioAnalysis(df,
sep = ";")
options(width = 100)
s <- summary(object = results,
k = 20,
pause = FALSE)##
##
## MAIN INFORMATION ABOUT DATA
##
## Timespan 2001 : 2020
## Sources (Journals, Books, etc) 1
## Documents 389
## Average years from publication 9.89
## Average citations per documents 4.087
## Average citations per year per doc 0.3347
## References 20101
##
## DOCUMENT TYPES
## article 371
## editorial 14
## letter 1
## note 1
## review 2
##
## DOCUMENT CONTENTS
## Keywords Plus (ID) 0
## Author's Keywords (DE) 649
##
## AUTHORS
## Authors 487
## Author Appearances 682
## Authors of single-authored documents 183
## Authors of multi-authored documents 304
##
## AUTHORS COLLABORATION
## Single-authored documents 229
## Documents per Author 0.799
## Authors per Document 1.25
## Co-Authors per Documents 1.75
## Collaboration Index 1.9
##
##
## Annual Scientific Production
##
## Year Articles
## 2001 16
## 2002 14
## 2003 16
## 2004 15
## 2005 19
## 2006 22
## 2007 18
## 2008 20
## 2009 26
## 2010 20
## 2011 20
## 2012 16
## 2013 19
## 2014 12
## 2015 24
## 2016 17
## 2017 24
## 2018 21
## 2019 21
## 2020 29
##
## Annual Percentage Growth Rate 3.179538
##
##
## Most Productive Authors
##
## Authors Articles Authors Articles Fractionalized
## 1 LEKSON SH 6 SEYMOUR DJ 5.00
## 2 SHACKLEY MS 6 STONE T 5.00
## 3 ADAMS KR 5 LEKSON SH 3.64
## 4 CREEL D 5 LYONS PD 3.50
## 5 REED PF 5 REED PF 3.33
## 6 ROTH BJ 5 BELLORADO BA 3.00
## 7 SEYMOUR DJ 5 COFFEY G 3.00
## 8 STONE T 5 NA NA 3.00
## 9 ALLISON JR 4 OSTERHOLTZ AJ 3.00
## 10 ANYON R 4 SNEAD JE 3.00
## 11 BELLORADO BA 4 WASHBURN DK 3.00
## 12 FERGUSON JR 4 WEBSTER LD 2.83
## 13 HARRY KG 4 ALLISON JR 2.67
## 14 HARTMANN WK 4 SHACKLEY MS 2.58
## 15 LYONS PD 4 ADAMS EC 2.50
## 16 NELSON MC 4 DEAN RM 2.50
## 17 WASHBURN DK 4 GEIB PR 2.50
## 18 WEBSTER LD 4 VAN DYKE RM 2.50
## 19 ABBOTT DR 3 WHITTLESEY SM 2.33
## 20 ADAMS EC 3 JANETSKI JC 2.20
##
##
## Top manuscripts per citations
##
## Paper DOI TC TCperYear NTC
## 1 CORDELL LS, 2007, KIVA 10.1179/kiv.2007.72.4.001 52 3.467 3.93
## 2 BENSON LV, 2009, KIVA 10.1179/kiv.2009.75.1.005 46 3.538 10.14
## 3 MALVILLE JM, 2001, KIVA 10.1080/00231940.2001.11758436 30 1.429 3.33
## 4 SANCHEZ MG, 2001, KIVA 10.1080/00231940.2001.11758451 28 1.333 3.11
## 5 GAINES EP, 2009, KIVA 10.1179/kiv.2009.74.3.003 25 1.923 5.51
## 6 LIEBMANN M, 2007, KIVA 10.1179/kiv.2007.73.2.006 25 1.667 1.89
## 7 POTTER JM, 2007, KIVA 10.1179/kiv.2007.72.4.002 25 1.667 1.89
## 8 LEKSON SH, 2002, KIVA 10.1080/00231940.2002.11758469 24 1.200 3.78
## 9 LAKATOS SA, 2007, KIVA 10.1179/kiv.2007.73.1.002 22 1.467 1.66
## 10 CHARLES MC, 2006, KIVA-a-b 10.1179/kiv.2006.72.2.003 22 1.375 2.88
## 11 KULISHECK J, 2003, KIVA 10.1080/00231940.2003.11758484 21 1.105 2.20
## 12 SCHILLACI MA, 2003, KIVA 10.1080/00231940.2003.11758476 21 1.105 2.20
## 13 MATSON RG, 2006, KIVA 10.1179/kiv.2006.72.2.002 20 1.250 2.62
## 14 BECK ME, 2006, KIVA 10.1179/kiv.2006.72.1.004 20 1.250 2.62
## 15 VANPOOL TL, 2006, KIVA 10.1179/kiv.2006.71.4.004 20 1.250 2.62
## 16 KANTNER J, 2003, KIVA-a 10.1080/00231940.2003.11758491 20 1.053 2.09
## 17 ROTH BJ, 2008, KIVA 10.1179/kiv.2008.73.3.004 19 1.357 6.91
## 18 VIERRA BJ, 2007, KIVA-a 10.1179/kiv.2007.73.2.002 19 1.267 1.44
## 19 CROWN PL, 2016, KIVA 10.1080/00231940.2016.1223981 18 3.000 6.24
## 20 DURAND KR, 2003, KIVA 10.1080/00231940.2003.11758489 17 0.895 1.78
##
##
## Corresponding Author's Countries
##
## Country Articles Freq SCP MCP MCP_Ratio
## 1 USA 217 0.93133 213 4 0.0184
## 2 MEXICO 8 0.03433 8 0 0.0000
## 3 CANADA 3 0.01288 0 3 1.0000
## 4 UNITED KINGDOM 2 0.00858 1 1 0.5000
## 5 NETHERLANDS 1 0.00429 0 1 1.0000
## 6 POLAND 1 0.00429 1 0 0.0000
## 7 SOUTH AFRICA 1 0.00429 0 1 1.0000
##
##
## SCP: Single Country Publications
##
## MCP: Multiple Country Publications
##
##
## Total Citations per Country
##
## Country Total Citations Average Article Citations
## 1 USA 955 4.40
## 2 MEXICO 24 3.00
## 3 CANADA 14 4.67
## 4 UNITED KINGDOM 6 3.00
## 5 NETHERLANDS 1 1.00
## 6 POLAND 1 1.00
## 7 SOUTH AFRICA 1 1.00
##
##
## Most Relevant Sources
##
## Sources Articles
## 1 KIVA 389
# plot attributes
plot(x = results,
k = 20,
pause = FALSE)
# calculate citations in local network
CR <- localCitations(df, sep = ";")
# top 20 cited authors in local network
CR$Authors[1:20,]## Author LocalCitations
## 77 CREEL D 11
## 225 KAMP-WHITTAKER A 7
## 289 MILLER MR 7
## 398 SHAFER HJ 7
## 352 REED PF 6
## 367 ROTH BJ 6
## 397 SHACKLEY MS 6
## 14 ANYON R 5
## 172 HARRY KG 5
## 215 JANETSKI JC 5
## 334 PEREZ DM 5
## 73 CORL K 4
## 103 DOLAN SG 4
## 131 FLAVIN KM 4
## 134 FORD RI 4
## 148 GILMAN PA 4
## 260 LOENDORF CR 4
## 287 MILLER KW 4
## 292 MINNIS P 4
## 333 PAWLOWICZ L 4
# top 20 cited papers in local network
CR$Papers[1:20,]## Paper DOI Year LCS GCS
## 363 LEKSON SH, 2002, KIVA 10.1080/00231940.2002.11758469 2002 7 24
## 283 POTTER JM, 2007, KIVA 10.1179/kiv.2007.72.4.002 2007 6 25
## 294 CHARLES MC, 2006, KIVA-a-b 10.1179/kiv.2006.72.2.003 2006 5 22
## 349 DURAND KR, 2003, KIVA 10.1080/00231940.2003.11758489 2003 5 17
## 135 MATSON RG, 2015, KIVA 10.1080/00231940.2016.1147162 2015 4 6
## 238 BENSON LV, 2009, KIVA 10.1179/kiv.2009.75.1.005 2009 4 46
## 277 LAKATOS SA, 2007, KIVA 10.1179/kiv.2007.73.1.002 2007 4 22
## 286 BERNARDINI W, 2007, KIVA 10.1179/kiv.2007.72.3.001 2007 4 16
## 291 CHARLES MC, 2006, KIVA-a 10.1179/kiv.2006.72.2.004 2006 4 13
## 293 MATSON RG, 2006, KIVA 10.1179/kiv.2006.72.2.002 2006 4 20
## 56 HARROD RP, 2018, KIVA 10.1080/00231940.2018.1528712 2018 3 3
## 77 ODONNELL A, 2017, KIVA 10.1080/00231940.2017.1386812 2017 3 5
## 83 ANYON R, 2017, KIVA 10.1080/00231940.2017.1341807 2017 3 6
## 97 CROWN PL, 2016, KIVA 10.1080/00231940.2016.1223981 2016 3 18
## 271 LIEBMANN M, 2007, KIVA 10.1179/kiv.2007.73.2.006 2007 3 25
## 290 HOVEZAK TD, 2006, KIVA 10.1179/kiv.2006.72.2.005 2006 3 8
## 359 SCHILLACI MA, 2003, KIVA 10.1080/00231940.2003.11758476 2003 3 21
## 369 STONE T, 2002, KIVA 10.1080/00231940.2002.11758464 2002 3 8
## 51 WALLER KD, 2018, KIVA 10.1080/00231940.2018.1538184 2018 2 2
## 53 FLEMING K, 2018, KIVA 10.1080/00231940.2018.1533196 2018 2 2
# top authors' productivity over time
topAU <- authorProdOverTime(df,
k = 20,
graph = TRUE)
# most cited references in global network
mcr <- citations(df,
field = "article",
sep = ";")
cbind(mcr$Cited[1:20])## [,1]
## ORTMAN, S.G., (2012) WINDS FROM THE NORTH: TEWA ORIGINS AND HISTORICAL ANTHROPOLOGY, , UNIVERSITY OF UTAH PRESS, SALT LAKE CITY 14
## LEBLANC, S.A., (1999) PREHISTORIC WARFARE IN THE AMERICAN SOUTHWEST, , UNIVERSITY OF UTAH PRESS, SALT LAKE CITY 13
## BERNARDINI, W., (2005) HOPI ORAL TRADITION AND THE ARCHAEOLOGY OF IDENTITY, , UNIVERSITY OF ARIZONA PRESS, TUCSON 10
## VARIEN, M.D., (1999) SEDENTISM AND MOBILITY IN A SOCIAL LANDSCAPE: MESA VERDE AND BEYOND, , UNIVERSITY OF ARIZONA PRESS, TUCSON 9
## LYNEIS, M.M., THE VIRGIN ANASAZI, FAR WESTERN PUEBLOANS (1995) JOURNAL OF WORLD PREHISTORY, 9 (2), PP. 199-241 8
## ARNOLD, D.E., (1985) CERAMIC THEORY AND CULTURAL PROCESS, , CAMBRIDGE UNIVERSITY PRESS, CAMBRIDGE 7
## CROWN, P.L., (1994) CERAMICS AND IDEOLOGY: SALADO POLYCHROME POTTERY, , UNIVERSITY OF NEW MEXICO PRESS, ALBUQUERQUE 7
## GEIB, P.R., (2011) FORAGERS AND FARMERS OF THE NORTHERN KAYENTA REGION: EXCAVATIONS ALONG THE NAVAJO MOUNTAIN ROAD, , UNIVERSITY OF UTAH PRESS, SALT LAKE CITY 6
## LIPE, W.D., THE DEPOPULATION OF THE NORTHERN SAN JUAN: CONDITIONS IN THE TURBULENT 1200S (1995) JOURNAL OF ANTHROPOLOGICAL ARCHAEOLOGY, 14, PP. 143-169 6
## MATSON, R.G., (1991) ORIGINS OF SOUTHWESTERN AGRICULTURE. UNIVERSITY OF ARIZONA PRESS, TUCSON., , THE 6
## SHAFER, H.J., (2003) MIMBRES ARCHAEOLOGY AT THE NAN RANCH RUIN, , UNIVERSITY OF NEW MEXICO PRESS, ALBUQUERQUE 6
## TYLER, H.A., (1979) PUEBLO BIRDS AND MYTHS, , UNIVERSITY OF OKLAHOMA PRESS, NORMAN 6
## WILSHUSEN, R.H., ORTMAN, S.G., RETHINKING THE PUEBLO I PERIOD IN THE SAN JUAN DRAINAGE: AGGREGATION, MIGRATION, AND CULTURAL DIVERSITY (1999) KIVA, 64 (3), PP. 369-399 6
## ADAMS, E.C., (1991) THE ORIGIN AND DEVELOPMENT OF THE PUEBLO KATSINA CULT, , UNIVERSITY OF ARIZONA PRESS, TUCSON 5
## HEGMON, M., RECENT ISSUES IN THE ARCHAEOLOGY OF THE MIMBRES REGION OF THE NORTH AMERICAN SOUTHWEST (2002) JOURNAL OF ARCHAEOLOGICAL RESEARCH, 10 (4), PP. 307-357 5
## KUCKELMAN, K.A., LIGHTFOOT, R.R., MARTIN, D.L., THE BIOARCHAEOLOGY AND TAPHONOMY OF VIOLENCE AT CASTLE ROCK AND SAND CANYON PUEBLOS, SOUTHWESTERN COLORADO (2002) AMERICAN ANTIQUITY, 67, PP. 486-513 5
## LEKSON, S.H., (1986) GREAT PUEBLO ARCHITECTURE OF CHACO CANYON, NEW MEXICO., , UNIVERSITY OF NEW MEXICO PRESS, ALBUQUERQUE 5
## LEKSON, S.H., CAMERON, C.M., THE ABANDONMENT OF CHACO CANYON, THE MESA VERDE MIGRATIONS, AND THE REORGANIZATION OF THE PUEBLO WORLD (1995) JOURNAL OF ANTHROPOLOGICAL ARCHAEOLOGY, 14, PP. 184-202 5
## LYONS, P.D., (2003) ANCESTRAL HOPI MIGRATIONS, , ANTHROPOLOGICAL PAPERS OF THE UNIVERSITY OF ARIZONA 68, UNIVERSITY OF ARIZONA PRESS, TUCSON 5
## MARTIN, D.L., HARD TIMES IN DRY LANDS: MAKING MEANING OF VIOLENCE IN THE ANCIENT SOUTHWEST (2016) JOURNAL OF ANTHROPOLOGICAL RESEARCH, 72 (1), PP. 1-23 5
# most cited authors in global network
mcr <- citations(df,
field = "author",
sep = ";")
cbind(mcr$Cited[1:20])## [,1]
## LEKSON S H 223
## HAURY E W 211
## VARIEN M D 183
## LIPE W D 164
## DEAN J S 159
## LEBLANC S A 154
## WILSHUSEN R H 150
## KOHLER T A 134
## ORTMAN S G 133
## MILLS B J 126
## CLARK J J 124
## WINDES T C 122
## NELSON M C 109
## CROWN P L 103
## HEGMON M 100
## MATSON R G 99
## WILCOX D R 97
## SEYMOUR D J 94
## KIDDER A V 92
## DOYEL D E 90
dom <- biblioAnalysis(df)
dom.r <- dominance(dom)
dom.r## Author Dominance Factor Tot Articles Single-Authored Multi-Authored First-Authored Rank by Articles Rank by DF
## 1 ROTH BJ 0.8000000 5 0 5 4 3 1
## 2 CREEL D 0.5000000 5 1 4 2 3 2
## 3 ALLISON JR 0.5000000 4 2 2 1 7 2
## 4 ANYON R 0.5000000 4 0 4 2 7 2
## 5 BELLORADO BA 0.5000000 4 2 2 1 7 2
## 6 LEKSON SH 0.3333333 6 3 3 1 1 6
## 7 REED PF 0.3333333 5 2 3 1 3 6
## 8 FERGUSON JR 0.2500000 4 0 4 1 7 8
## 9 SHACKLEY MS 0.2000000 6 1 5 1 1 9
## 10 ADAMS KR 0.2000000 5 0 5 1 3 9
Co-citation analysis is the most commonly used bibliometric analysis method (Ding, Chowdhury, and Foo 2001), and is defined as two publications that are cited together in one article (Small 1973).
# extract author names from reference items
df <- metaTagExtraction(df,
Field = "CR_AU")
# author co-citation network
auth.co.mat <- biblioNetwork(df,
analysis = "co-citation",
network = "authors",
sep = ";")
# network plot
auth.co.net = networkPlot(auth.co.mat,
n = 50,
Title = "Author Co-Citation Network",
type = "auto",
size = 10,
size.cex = T,
remove.multiple = FALSE,
labelsize = 0.5,
edgesize = 8,
edges.min = 3,
remove.isolates = TRUE)
# descriptive analysis of author co-citation network
auth.co.netstat <- networkStat(auth.co.mat)
summary(auth.co.netstat, k = 15)##
##
## Main statistics about the network
##
## Size 4564
## Density 0.029
## Transitivity 0.278
## Diameter 3
## Degree Centralization 0.418
## Average path length 2.14
##
Coupling is a similarity measure that uses citation analysis to illustrate a similarity relationship between documents. Author coupling occurs when two authors reference a common third author in their bibliographies.
# author coupling network
auth.coup.mat <- biblioNetwork(df,
analysis = "coupling",
network = "authors",
sep = ";")
# network plot
auth.coup.net = networkPlot(auth.coup.mat,
n = 50,
Title = "Author Coupling Network",
type = "mds",
size = 10,
size.cex = T,
remove.multiple = FALSE,
labelsize = 0.5,
edgesize = 5,
edges.min = 8,
remove.isolates = TRUE)
# descriptive analysis of author coupling network
auth.coup.netstat <- networkStat(auth.coup.mat)
summary(auth.coup.netstat, k = 15)##
##
## Main statistics about the network
##
## Size 487
## Density 0.151
## Transitivity 0.461
## Diameter 4
## Degree Centralization 0.353
## Average path length 1.976
##
The historiographic map is a chronological network map of the most relevant direct citations resulting from this bibliographic collection.
# historical citation network
options(width = 100)
histResults <- histNetwork(df,
min.citations = 25,
sep = ";")##
## SCOPUS DB: Searching local citations (LCS) by document titles (TI) and DOIs...
##
## Found 6 documents with no empty Local Citations (LCS)
# plot historical co-citation network
hnet <- histPlot(histResults,
n = 100,
size = 6,
labelsize = 2)
##
## Legend
##
## Label DOI Year LCS GCS
## 1 BENSON LV, 2009, KIVA 10.1179/kiv.2009.75.1.005 2009 4 46
## 2 LIEBMANN M, 2007, KIVA 10.1179/kiv.2007.73.2.006 2007 3 25
## 3 CORDELL LS, 2007, KIVA 10.1179/kiv.2007.72.4.001 2007 2 52
## 4 POTTER JM, 2007, KIVA 10.1179/kiv.2007.72.4.002 2007 6 25
## 5 SANCHEZ MG, 2001, KIVA 10.1080/00231940.2001.11758451 2001 1 28
## 6 MALVILLE JM, 2001, KIVA 10.1080/00231940.2001.11758436 2001 2 30
## 7 BURRILLO RE, 2017, KIVA 10.1080/00231940.2017.1309109 2017 0 1
## 8 PLOG S, 2015, KIVA 10.1080/00231940.2015.1127117 2015 0 5
## 9 MATSON RG, 2015, KIVA 10.1080/00231940.2016.1147162 2015 0 6
## 10 BELLORADO BA, 2013, KIVA-a <NA> NA NA NA
## 11 DALE E, 2020, KIVA 10.1080/00231940.2020.1747793 2020 0 0
## 12 WHITNEY K, 2017, KIVA 10.1080/00231940.2017.1336970 2017 0 1
## 13 GRUNER E, 2013, KIVA 10.1179/0023194013Z.0000000004 2013 0 1
## 14 PAILES MC, 2015, KIVA 10.1080/00231940.2016.1147148 2015 0 0
## 15 SINENSKY RJ, 2019, KIVA 10.1080/00231940.2019.1577059 2019 0 0
## 16 MILLER K, 2018, KIVA 10.1080/00231940.2018.1443544 2018 0 0
## 17 INGRAM SE, 2015, KIVA 10.1080/00231940.2015.1118736 2015 0 2
## 18 BROWN GM, 2013, KIVA 10.1179/0023194013Z.0000000008 2013 0 6
## 19 BELLORADO BA, 2013, KIVA 10.1179/0023194013Z.0000000006 2013 0 7
## 20 BELLORADO BA, 2013, KIVA 10.1179/0023194013Z.0000000007 2013 0 11
## 21 MILLER KW, 2016, KIVA 10.1080/00231940.2016.1179548 2016 0 1
## 22 JANES SD, 2017, KIVA 10.1080/00231940.2016.1271261 2017 0 0
## 23 DOXTATER D, 2002, KIVA 10.1080/00231940.2002.11758467 2002 0 11
topKW = KeywordGrowth(df,
Tag = "DE",
sep = ";",
top = 10,
cdf = TRUE)
topKW## Year MIGRATION RITUAL CHACO CANYON HISTORICAL ARCHAEOLOGY SOUTHWEST ANCESTRAL PUEBLO
## 1 2014 1 0 0 0 0 0
## 2 2015 1 4 1 0 1 0
## 3 2016 3 4 1 0 3 1
## 4 2017 5 4 3 0 4 3
## 5 2018 5 8 6 0 5 4
## 6 2019 8 8 6 0 6 5
## 7 2020 10 9 8 8 8 7
## AMERICAN SOUTHWEST HOHOKAM MIMBRES US SOUTHWEST
## 1 1 0 1 0
## 2 1 2 3 1
## 3 1 2 3 2
## 4 2 2 3 3
## 5 3 2 5 4
## 6 3 2 5 4
## 7 6 6 6 6
# plot results
key.plot = melt(topKW,
id ='Year')
ggplot(key.plot, aes(Year,
value,
group = variable,
color = variable)) +
geom_line()
The co-word analysis maps the conceptual structure of a research domain using the co-occurrence of author keywords in the bibliographic collection.
# using authors keywords
cw <- conceptualStructure(df,
field = "DE",
method = "MDS",
minDegree = 2,
clust = "auto",
stemming = FALSE,
labelsize = 10,
documents = 50)
From (Cobo et al. 2011, 150–51):
- Themes in the upper-right quadrant are both well developed and important for the structuring ofa research field. They are known as the motor-themes of the specialty, given that they present strong centrality and high density. The placement of themesin this quadrantimplies that theyare related externally to concepts applicable to otherthemesthat are conceptually closely related.
- Themes in the upper-left quadrant have well developed internal ties but unimportant external ties and so are of only marginal importance for the field. These themes are very specialized and peripheral in character.
- Themes in the lower-left quadrant are both weakly developed and marginal. The themes ofthis quadrant have low density and low centrality, mainly representing either emerging or disappearing themes.
- Themes in the lower-right quadrant are important for a research field but are not developed. So, this quadrant groups transversal and general, basic themes.
# keyword map
map1 = thematicMap(df,
field = "DE",
n = 1000,
minfreq = 3,
stemming = FALSE,
size = 0.8,
n.labels = 1,
repel = TRUE)
# plot map
plot(map1$map)
Scientific collaborations are plotted where nodes are authors and links are co-authorships, illustrating collaborations between authors.
# author collaboration network
auth.collab <- biblioNetwork(df,
analysis = "collaboration",
network = "authors",
sep = ";")
# network plot
auth.collabnet = networkPlot(auth.collab,
n = 100,
Title = "Author Collaboration",
type = "mds",
size = 20,
size.cex = T,
edgesize = 2,
labelsize = 0.5,
remove.multiple = TRUE,
remove.isolates = TRUE)
# descriptive analysis of author collaboration network
auth.collab.netstat <- networkStat(auth.collab)
summary(auth.collab.netstat, k = 15)##
##
## Main statistics about the network
##
## Size 487
## Density 0.005
## Transitivity 0.709
## Diameter 10
## Degree Centralization 0.032
## Average path length 3.121
##
Scientific collaborations are plotted where nodes are institutions and links are co-authorships, illustrating collaborations between institutions.
# author collaboration network
edu.collab <- biblioNetwork(df,
analysis = "collaboration",
network = "universities",
sep = ";")
# network plot
edu.collabnet = networkPlot(edu.collab,
n = 100,
Title = "Edu Collaboration",
type = "auto",
size = 30,
size.cex = T,
edgesize = 2,
labelsize = 0.4,
remove.isolates = TRUE)
# descriptive analysis of edu collaboration network
edu.collab.netstat<-networkStat(edu.collab)
summary(edu.collab.netstat, k = 15)##
##
## Main statistics about the network
##
## Size 249
## Density 0.008
## Transitivity 0.477
## Diameter 10
## Degree Centralization 0.077
## Average path length 3.669
##
# country collaboration network
count <- metaTagExtraction(df,
Field = "AU_CO",
sep = ";")
cmat1 <- biblioNetwork(count,
analysis = "collaboration",
network = "countries",
sep = ";")
# network plot
cnet1 = networkPlot(cmat1,
n = dim(cmat1)[1],
Title = "Country Collaboration",
type = "circle",
size = 10,
size.cex = T,
edgesize = 1,
labelsize = 0.6,
cluster = "none")
In this figure, scientific collaborations are plotted where nodes are countries and links are co-authorships, illustrating collaborations between countries
# descriptive analysis of country collaboration network
countnetstat <- networkStat(cmat1)
summary(countnetstat, k = 15)##
##
## Main statistics about the network
##
## Size 9
## Density 0.25
## Transitivity 0.24
## Diameter 2
## Degree Centralization 0.625
## Average path length 1.679
##
This version of the analysis was generated on 2021-05-20 08:29:45 using the following computational environment and dependencies:
# what R packages and versions were used?
if ("devtools" %in% installed.packages()) devtools::session_info()## - Session info -----------------------------------------------------------------------------------
## setting value
## version R version 4.0.5 (2021-03-31)
## os Windows 10 x64
## system x86_64, mingw32
## ui RTerm
## language (EN)
## collate English_United States.1252
## ctype English_United States.1252
## tz America/Chicago
## date 2021-05-20
##
## - Packages ---------------------------------------------------------------------------------------
## package * version date lib source
## abind 1.4-5 2016-07-21 [1] CRAN (R 4.0.0)
## assertthat 0.2.1 2019-03-21 [1] CRAN (R 4.0.2)
## backports 1.2.1 2020-12-09 [1] CRAN (R 4.0.3)
## bibliometrix * 3.1.1 2021-05-20 [1] Github (massimoaria/bibliometrix@2a7b6b8)
## bibliometrixData 0.1.0 2020-12-10 [1] CRAN (R 4.0.3)
## broom 0.7.6 2021-04-05 [1] CRAN (R 4.0.4)
## cachem 1.0.4 2021-02-13 [1] CRAN (R 4.0.4)
## callr 3.7.0 2021-04-20 [1] CRAN (R 4.0.4)
## car 3.0-10 2020-09-29 [1] CRAN (R 4.0.3)
## carData 3.0-4 2020-05-22 [1] CRAN (R 4.0.0)
## cellranger 1.1.0 2016-07-27 [1] CRAN (R 4.0.2)
## cli 2.5.0 2021-04-26 [1] CRAN (R 4.0.5)
## cluster 2.1.1 2021-02-14 [2] CRAN (R 4.0.5)
## colorspace 2.0-1 2021-05-04 [1] CRAN (R 4.0.5)
## crayon 1.4.1 2021-02-08 [1] CRAN (R 4.0.3)
## curl 4.3.1 2021-04-30 [1] CRAN (R 4.0.5)
## data.table 1.14.0 2021-02-21 [1] CRAN (R 4.0.4)
## DBI 1.1.1 2021-01-15 [1] CRAN (R 4.0.3)
## dendextend 1.15.1 2021-05-08 [1] CRAN (R 4.0.5)
## desc 1.3.0 2021-03-05 [1] CRAN (R 4.0.4)
## devtools 2.4.1 2021-05-05 [1] CRAN (R 4.0.5)
## digest 0.6.27 2020-10-24 [1] CRAN (R 4.0.3)
## dimensionsR 0.0.2 2020-08-28 [1] CRAN (R 4.0.3)
## dplyr 1.0.6 2021-05-05 [1] CRAN (R 4.0.5)
## DT 0.18 2021-04-14 [1] CRAN (R 4.0.4)
## ellipsis 0.3.2 2021-04-29 [1] CRAN (R 4.0.5)
## evaluate 0.14 2019-05-28 [1] CRAN (R 4.0.2)
## factoextra 1.0.7 2020-04-01 [1] CRAN (R 4.0.3)
## FactoMineR 2.4 2020-12-11 [1] CRAN (R 4.0.3)
## fansi 0.4.2 2021-01-15 [1] CRAN (R 4.0.3)
## farver 2.1.0 2021-02-28 [1] CRAN (R 4.0.4)
## fastmap 1.1.0 2021-01-25 [1] CRAN (R 4.0.3)
## flashClust 1.01-2 2012-08-21 [1] CRAN (R 4.0.3)
## forcats 0.5.1 2021-01-27 [1] CRAN (R 4.0.3)
## foreign 0.8-81 2020-12-22 [2] CRAN (R 4.0.5)
## fs 1.5.0 2020-07-31 [1] CRAN (R 4.0.2)
## generics 0.1.0 2020-10-31 [1] CRAN (R 4.0.3)
## ggnetwork 0.5.8 2020-02-12 [1] CRAN (R 4.0.5)
## ggplot2 * 3.3.3 2020-12-30 [1] CRAN (R 4.0.3)
## ggpubr 0.4.0 2020-06-27 [1] CRAN (R 4.0.2)
## ggrepel 0.9.1 2021-01-15 [1] CRAN (R 4.0.3)
## ggsignif 0.6.1 2021-02-23 [1] CRAN (R 4.0.4)
## glue 1.4.2 2020-08-27 [1] CRAN (R 4.0.2)
## gridExtra 2.3 2017-09-09 [1] CRAN (R 4.0.2)
## gtable 0.3.0 2019-03-25 [1] CRAN (R 4.0.2)
## haven 2.4.1 2021-04-23 [1] CRAN (R 4.0.5)
## here * 1.0.1 2020-12-13 [1] CRAN (R 4.0.3)
## highr 0.9 2021-04-16 [1] CRAN (R 4.0.4)
## hms 1.1.0 2021-05-17 [1] CRAN (R 4.0.5)
## htmltools 0.5.1.1 2021-01-22 [1] CRAN (R 4.0.3)
## htmlwidgets 1.5.3 2020-12-10 [1] CRAN (R 4.0.3)
## httpuv 1.6.1 2021-05-07 [1] CRAN (R 4.0.5)
## httr 1.4.2 2020-07-20 [1] CRAN (R 4.0.2)
## igraph 1.2.6 2020-10-06 [1] CRAN (R 4.0.3)
## janeaustenr 0.1.5 2017-06-10 [1] CRAN (R 4.0.5)
## jsonlite 1.7.2 2020-12-09 [1] CRAN (R 4.0.3)
## knitr 1.33 2021-04-24 [1] CRAN (R 4.0.5)
## labeling 0.4.2 2020-10-20 [1] CRAN (R 4.0.3)
## later 1.2.0 2021-04-23 [1] CRAN (R 4.0.5)
## lattice 0.20-41 2020-04-02 [2] CRAN (R 4.0.5)
## lazyeval 0.2.2 2019-03-15 [1] CRAN (R 4.0.2)
## leaps 3.1 2020-01-16 [1] CRAN (R 4.0.3)
## lifecycle 1.0.0 2021-02-15 [1] CRAN (R 4.0.4)
## magrittr 2.0.1 2020-11-17 [1] CRAN (R 4.0.3)
## MASS 7.3-54 2021-05-03 [1] CRAN (R 4.0.5)
## Matrix 1.3-3 2021-05-04 [1] CRAN (R 4.0.5)
## memoise 2.0.0 2021-01-26 [1] CRAN (R 4.0.3)
## mime 0.10 2021-02-13 [1] CRAN (R 4.0.4)
## munsell 0.5.0 2018-06-12 [1] CRAN (R 4.0.2)
## openxlsx 4.2.3 2020-10-27 [1] CRAN (R 4.0.3)
## pillar 1.6.1 2021-05-16 [1] CRAN (R 4.0.5)
## pkgbuild 1.2.0 2020-12-15 [1] CRAN (R 4.0.3)
## pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.0.2)
## pkgload 1.2.1 2021-04-06 [1] CRAN (R 4.0.5)
## plotly 4.9.3 2021-01-10 [1] CRAN (R 4.0.3)
## plyr 1.8.6 2020-03-03 [1] CRAN (R 4.0.2)
## prettyunits 1.1.1 2020-01-24 [1] CRAN (R 4.0.2)
## processx 3.5.2 2021-04-30 [1] CRAN (R 4.0.5)
## promises 1.2.0.1 2021-02-11 [1] CRAN (R 4.0.3)
## ps 1.6.0 2021-02-28 [1] CRAN (R 4.0.4)
## pubmedR 0.0.3 2020-07-09 [1] CRAN (R 4.0.3)
## purrr 0.3.4 2020-04-17 [1] CRAN (R 4.0.2)
## R6 2.5.0 2020-10-28 [1] CRAN (R 4.0.3)
## RColorBrewer 1.1-2 2014-12-07 [1] CRAN (R 4.0.0)
## Rcpp 1.0.6 2021-01-15 [1] CRAN (R 4.0.3)
## readr 1.4.0 2020-10-05 [1] CRAN (R 4.0.3)
## readxl 1.3.1 2019-03-13 [1] CRAN (R 4.0.2)
## remotes 2.3.0 2021-04-01 [1] CRAN (R 4.0.5)
## rentrez 1.2.3 2020-11-10 [1] CRAN (R 4.0.3)
## reshape2 * 1.4.4 2020-04-09 [1] CRAN (R 4.0.3)
## rio 0.5.26 2021-03-01 [1] CRAN (R 4.0.4)
## rlang 0.4.11 2021-04-30 [1] CRAN (R 4.0.5)
## rmarkdown 2.8 2021-05-07 [1] CRAN (R 4.0.5)
## rprojroot 2.0.2 2020-11-15 [1] CRAN (R 4.0.3)
## rscopus 0.6.6 2019-09-17 [1] CRAN (R 4.0.3)
## rstatix 0.7.0 2021-02-13 [1] CRAN (R 4.0.4)
## scales 1.1.1 2020-05-11 [1] CRAN (R 4.0.2)
## scatterplot3d 0.3-41 2018-03-14 [1] CRAN (R 4.0.3)
## sessioninfo 1.1.1 2018-11-05 [1] CRAN (R 4.0.2)
## shiny 1.6.0 2021-01-25 [1] CRAN (R 4.0.3)
## SnowballC 0.7.0 2020-04-01 [1] CRAN (R 4.0.3)
## stringdist 0.9.6.3 2020-10-09 [1] CRAN (R 4.0.3)
## stringi 1.6.2 2021-05-17 [1] CRAN (R 4.0.5)
## stringr 1.4.0 2019-02-10 [1] CRAN (R 4.0.2)
## testthat 3.0.2 2021-02-14 [1] CRAN (R 4.0.4)
## tibble 3.1.2 2021-05-16 [1] CRAN (R 4.0.5)
## tidyr 1.1.3 2021-03-03 [1] CRAN (R 4.0.4)
## tidyselect 1.1.1 2021-04-30 [1] CRAN (R 4.0.5)
## tidytext 0.3.1 2021-04-10 [1] CRAN (R 4.0.5)
## tokenizers 0.2.1 2018-03-29 [1] CRAN (R 4.0.5)
## usethis 2.0.1 2021-02-10 [1] CRAN (R 4.0.3)
## utf8 1.2.1 2021-03-12 [1] CRAN (R 4.0.4)
## vctrs 0.3.8 2021-04-29 [1] CRAN (R 4.0.5)
## viridis 0.6.1 2021-05-11 [1] CRAN (R 4.0.5)
## viridisLite 0.4.0 2021-04-13 [1] CRAN (R 4.0.5)
## withr 2.4.2 2021-04-18 [1] CRAN (R 4.0.4)
## xfun 0.22 2021-03-11 [1] CRAN (R 4.0.4)
## XML 3.99-0.6 2021-03-16 [1] CRAN (R 4.0.4)
## xtable 1.8-4 2019-04-21 [1] CRAN (R 4.0.2)
## yaml 2.2.1 2020-02-01 [1] CRAN (R 4.0.0)
## zip 2.1.1 2020-08-27 [1] CRAN (R 4.0.2)
##
## [1] C:/Users/seldenjrz/Documents/R/win-library/4.0
## [2] C:/Program Files/R/R-4.0.5/library
Current Git commit details are:
# where can I find this commit?
if ("git2r" %in% installed.packages() & git2r::in_repository(path = ".")) git2r::repository(here::here()) ## Local: main D:/github/kivabib
## Remote: main @ origin (https://github.com/aksel-blaise/kivabib)
## Head: [c6da080] 2021-05-20: Initial commit
Aria, Massimo, and Corrado Cuccurullo. 2017. “Bibliometrix : An r-Tool for Comprehensive Science Mapping Analysis.” Journal of Informetrics 11 (4): 959–75. https://doi.org/10.1016/j.joi.2017.08.007.
Cobo, M. J., A. G. López-Herrera, E. Herrera-Viedma, and F. Herrera. 2011. “An Approach for Detecting, Quantifying, and Visualizing the Evolution of a Research Field: A Practical Application to the Fuzzy Sets Theory Field.” Journal Article. Journal of Informetrics 5 (1): 146–66. https://doi.org/10.1016/j.joi.2010.10.002.
Ding, Ying, Gobinda G. Chowdhury, and Schubert Foo. 2001. “Bibliometric Cartography of Information Retrieval Research by Using Co-Word Analysis.” Information Processing & Management 37 (6): 817–42. https://doi.org/10.1016/s0306-4573(00)00051-0.
Small, Henry. 1973. “Co-Citation in the Scientific Literature: A New Measure of the Relationship Between Two Documents.” Journal of the American Society for Information Science 24 (4): 265–69. https://doi.org/10.1002/asi.4630240406.