CRAN Release 4.1.4

Author: massimoaria

.Rbuildignore

@@ -22,3 +22,5 @@ Rubbish
 ^inst/biblioshiny/rsconnect
 ^rsconnect
 
+^CRAN-SUBMISSION$
+^cran-comments\.md$

NEWS

@@ -1,13 +1,16 @@
-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
    - Added OpenAlex algorithm to match local citations
    - 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)
 

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).

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){

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

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.
 #'
 #' 

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 [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)
+#> 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,