diff --git a/.Rbuildignore b/.Rbuildignore index 1a932a77..5c9af37a 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -22,3 +22,5 @@ Rubbish ^inst/biblioshiny/rsconnect ^rsconnect +^CRAN-SUBMISSION$ +^cran-comments\.md$ diff --git a/NEWS b/NEWS index 73b68227..730f8551 100644 --- a/NEWS +++ b/NEWS @@ -1,6 +1,7 @@ -bibliometrix v4.1.4 (Release date: ) +bibliometrix v4.1.4 (Release date: 2023-11-29) Changes: +* Biblioshiny: After the data quality check, the menus of the analyses that cannot be performed are hidden * Start to adding support to OpenAlex data * Improvements in historiograph: - Improved Scopus algorithm to match local citations @@ -8,6 +9,8 @@ Changes: - Added Lens.org algorithm to match local citations * Improved pajek export in biblioshiny * Computational speed improvements +* Solved issue with igraph 1.6.0 release canddate +* Solved issue with Matrix package bibliometrix v4.1.2 (Release date: 2023-03-06) diff --git a/R/couplingMap.R b/R/couplingMap.R index 394a79c9..996747fa 100644 --- a/R/couplingMap.R +++ b/R/couplingMap.R @@ -22,7 +22,7 @@ #' @param impact.measure is a character. It indicates the impact measure used to rank cluster elements (documents, authors or sources). #' It can be \code{impact.measure = c("local", "global")}.\\ #' With \code{impact.measure = "local"}, \link{couplingMap} calculates elements impact using the Normalized Local Citation Score while -#' using code{impact.measure = "global"}, the function uses the Normalized Global Citation Score to measure elements impact. +#' using \code{impact.measure = "global"}, the function uses the Normalized Global Citation Score to measure elements impact. #' @param minfreq is a integer. It indicates the minimum frequency (per thousand) of a cluster. It is a number in the range (0,1000). #' @param community.repulsion is a real. It indicates the repulsion force among network communities. It is a real number between 0 and 1. Default is \code{community.repulsion = 0.1}. #' @param stemming is logical. If it is TRUE the word (from titles or abstracts) will be stemmed (using the Porter's algorithm). diff --git a/R/csvScopus2df.R b/R/csvScopus2df.R index 7e994f14..62224683 100644 --- a/R/csvScopus2df.R +++ b/R/csvScopus2df.R @@ -29,6 +29,10 @@ csvScopus2df <- function(file){ DATA$AU=gsub("\\.", "", DATA$AU) DATA$AU=gsub(",", ";", DATA$AU) + ### store raw affiliation format to extract link among authors and affiliations + DATA$C1raw <- DATA$C1 + ### + # Affiliation if (!("C1" %in% names(DATA))){DATA$C1 <- NA}else{ DATA$C1 <- unlist(lapply(strsplit(DATA$C1,";"), function(l){ diff --git a/R/isi2df.R b/R/isi2df.R index 62735d5c..7d6fee71 100644 --- a/R/isi2df.R +++ b/R/isi2df.R @@ -64,6 +64,10 @@ Please, take a look at the vignettes: df <- cbind(df1,df2) rm(df1,df2) + ### store raw affiliation format to extract link among authors and affiliations + df$C1raw <- df$C1 + ### + df$DB <- "ISI" # Authors diff --git a/R/normalizeCItationScore.R b/R/normalizeCItationScore.R index e530309f..f76ac1ed 100644 --- a/R/normalizeCItationScore.R +++ b/R/normalizeCItationScore.R @@ -18,7 +18,7 @@ #' @param impact.measure is a character. It indicates the impact measure used to rank cluster elements (documents, authors or sources). #' It can be \code{impact.measure = c("local", "global")}.\\ #' With \code{impact.measure = "local"}, \link{normalizeCitationScore} calculates elements impact using the Normalized Local Citation Score while -#' using code{impact.measure = "global"}, the function uses the Normalized Global Citation Score to measure elements impact. +#' using \code{impact.measure = "global"}, the function uses the Normalized Global Citation Score to measure elements impact. #' @return a dataframe. #' #' diff --git a/README.md b/README.md index 442c828d..59239a7c 100644 --- a/README.md +++ b/README.md @@ -120,23 +120,23 @@ Load `bibliometrix` ``` r library('bibliometrix') -#> To cite bibliometrix in publications, please use: +#> Please note that our software is open source and available for use, distributed under the MIT license. +#> When it is used in a publication, we ask that authors properly cite the following reference: #> #> 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 +#> Journal of Informetrics, 11(4), pp 959-975, Elsevier. #> +#> Failure to properly cite the software is considered a violation of the license. #> #> For information and bug reports: +#> - Take a look at https://www.bibliometrix.org #> - 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) +#> Help us to keep Bibliometrix and Biblioshiny 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: +#> To start with the Biblioshiny app, please digit: #> biblioshiny() ``` @@ -197,23 +197,22 @@ The argument *M* is a bibliographic data frame obtained by com <- missingData(M) com$mandatoryTags -#> tag description missing_counts missing_pct status -#> 1 AU Author 0 0.00 Excellent -#> 2 DT Document Type 0 0.00 Excellent -#> 3 SO Journal 0 0.00 Excellent -#> 4 LA Language 0 0.00 Excellent -#> 5 NR Number of Cited References 0 0.00 Excellent -#> 6 WC Science Categories 0 0.00 Excellent -#> 7 TI Title 0 0.00 Excellent -#> 8 TC Total Citation 0 0.00 Excellent -#> 9 CR Cited References 2 0.22 Good -#> 10 AB Abstract 7 0.78 Good -#> 11 PY Publication Year 9 1.00 Good -#> 12 RP Corresponding Author 10 1.11 Good -#> 13 C1 Affiliation 21 2.34 Good -#> 14 DI DOI 36 4.01 Good -#> 15 DE Keywords 79 8.80 Good -#> 16 ID Keywords Plus 97 10.80 Acceptable +#> tag description missing_counts missing_pct status +#> 1 AU Author 0 0.00 Excellent +#> 2 DT Document Type 0 0.00 Excellent +#> 3 SO Journal 0 0.00 Excellent +#> 4 LA Language 0 0.00 Excellent +#> 5 WC Science Categories 0 0.00 Excellent +#> 6 TI Title 0 0.00 Excellent +#> 7 TC Total Citation 0 0.00 Excellent +#> 8 CR Cited References 2 0.22 Good +#> 9 AB Abstract 7 0.78 Good +#> 10 PY Publication Year 9 1.00 Good +#> 11 RP Corresponding Author 10 1.11 Good +#> 12 C1 Affiliation 21 2.34 Good +#> 13 DI DOI 36 4.01 Good +#> 14 DE Keywords 79 8.80 Good +#> 15 ID Keywords Plus 97 10.80 Acceptable ``` **missingData** returns a list containing two data frame. The first one, diff --git a/man/couplingMap.Rd b/man/couplingMap.Rd index 935c61df..f860347e 100644 --- a/man/couplingMap.Rd +++ b/man/couplingMap.Rd @@ -39,7 +39,7 @@ An n-gram is a contiguous sequence of n terms. The function can extract n-grams \item{impact.measure}{is a character. It indicates the impact measure used to rank cluster elements (documents, authors or sources). It can be \code{impact.measure = c("local", "global")}.\\ With \code{impact.measure = "local"}, \link{couplingMap} calculates elements impact using the Normalized Local Citation Score while -using code{impact.measure = "global"}, the function uses the Normalized Global Citation Score to measure elements impact.} +using \code{impact.measure = "global"}, the function uses the Normalized Global Citation Score to measure elements impact.} \item{minfreq}{is a integer. It indicates the minimum frequency (per thousand) of a cluster. It is a number in the range (0,1000).} diff --git a/man/figures/README-Co-Word Analysis-1.png b/man/figures/README-Co-Word Analysis-1.png index 30687321..3c3c6f2d 100644 Binary files a/man/figures/README-Co-Word Analysis-1.png and b/man/figures/README-Co-Word Analysis-1.png differ diff --git a/man/figures/README-Co-Word Analysis-2.png b/man/figures/README-Co-Word Analysis-2.png index 391b62e1..0d6045f4 100644 Binary files a/man/figures/README-Co-Word Analysis-2.png and b/man/figures/README-Co-Word Analysis-2.png differ diff --git a/man/figures/README-Co-citation network-1.png b/man/figures/README-Co-citation network-1.png index 2958d993..5966589d 100644 Binary files a/man/figures/README-Co-citation network-1.png and b/man/figures/README-Co-citation network-1.png differ diff --git a/man/figures/README-Country collaboration-1.png b/man/figures/README-Country collaboration-1.png index 2d29547f..0c24cf6c 100644 Binary files a/man/figures/README-Country collaboration-1.png and b/man/figures/README-Country collaboration-1.png differ diff --git a/man/figures/README-Historical Co-citation network-1.png b/man/figures/README-Historical Co-citation network-1.png index b13bbaa0..8bf2d952 100644 Binary files a/man/figures/README-Historical Co-citation network-1.png and b/man/figures/README-Historical Co-citation network-1.png differ diff --git a/man/figures/README-Keyword c-occurrences-1.png b/man/figures/README-Keyword c-occurrences-1.png index dfcd8ffb..b6511f86 100644 Binary files a/man/figures/README-Keyword c-occurrences-1.png and b/man/figures/README-Keyword c-occurrences-1.png differ diff --git a/man/normalizeCitationScore.Rd b/man/normalizeCitationScore.Rd index 97644429..4d0a4735 100644 --- a/man/normalizeCitationScore.Rd +++ b/man/normalizeCitationScore.Rd @@ -14,7 +14,7 @@ normalizeCitationScore(M, field = "documents", impact.measure = "local") \item{impact.measure}{is a character. It indicates the impact measure used to rank cluster elements (documents, authors or sources). It can be \code{impact.measure = c("local", "global")}.\\ With \code{impact.measure = "local"}, \link{normalizeCitationScore} calculates elements impact using the Normalized Local Citation Score while -using code{impact.measure = "global"}, the function uses the Normalized Global Citation Score to measure elements impact.} +using \code{impact.measure = "global"}, the function uses the Normalized Global Citation Score to measure elements impact.} } \value{ a dataframe.