_Bibliography.Rmd

# Bibliography


A brief introduction to bibliometrix


https://cran.r-project.org/web/packages/bibliometrix/vignettes/bibliometrix-vignette.html

 Bibliographic Network Visualization for Academic Literature Reviews 
 
 http://www.mburnamfink.com/blog/bibliographic-network-visualization-for-academic-literature-reviews
 
 
 https://embed.kumu.io/0b991b02bb20975fde904f4bf7433333#jpsp-top-50?s=%23doi-101037-0022-35147451252
 
  More Than Words? Computer-Aided Text Analysis in Organizational Behavior and Psychology Research
  
  https://www.annualreviews.org/doi/10.1146/annurev-orgpsych-032117-104622
  
  
 
 
 https://www.kumu.io/nicholasjkelley/jpsp-top-50
 
 
# knitcitations

https://github.com/cboettig/knitcitations


```
{r eval=FALSE, include=FALSE, echo=TRUE}
# library(devtools)
# install_github( cboettig/knitcitations )
install.packages( knitcitations )
```


```
{r eval=FALSE, include=FALSE, echo=TRUE}
library( knitcitations )
cleanbib()
options( citation_format  =  pandoc )
```


```
{r eval=FALSE, include=FALSE, echo=TRUE}
knitcitations::citep( 10.1890/11-0011.1 )
```


```
citation  r citep( 10.1890/11-0011.1 )  in text
```


```
{r eval=FALSE, include=FALSE, echo=TRUE}
knitcitations::citet( 10.1098/rspb.2013.1372 )
```



```
citation  r citet( 10.1098/rspb.2013.1372 )  in text
```

```
{r eval=FALSE, include=FALSE, echo=TRUE}
knitcitations::citep( http://knowledgeblog.org/greycite )
```


```
write.bibtex(file= references.bib )
```


# rcrossref

https://github.com/ropensci/rcrossref



# rorcid tutorial

https://ropensci.org/tutorials/rorcid_tutorial/



# rentrez tutorial

https://ropensci.org/tutorials/rentrez_tutorial/  

# WebSciCorpus

https://www.clarehooper.net/WebSciCorpus/

# WEB OF SCIENCE (WOS) CORPUS | PARSING SCRIPT

https://docs.cortext.net/question/web-of-science-wos-corpus-parsing-script-2/

# T-LAB PLUS 2019

https://tlab.it/en/allegati/help_en_online/mmappe2.htm

# Tools for bibliometric analyses

https://ju.se/library/research--teaching-support/bibliometrics/tools-for-bibliometric-analyses.html


# evidencepartners

https://www.evidencepartners.com/

# R script for creating a cross-citation network

https://www.researchgate.net/publication/327790285_R_script_for_creating_a_cross-citation_network

Repository: https://github.com/arsiders/citation-network



```
# RCitation - Quick Citation Network 
# Fall 2018 
# A.R. Siders (siders@alumni.stanford.edu)

# Creates a network of the citations among a set of academic papers. 
# Rationale: If full title of Article 2 is present in text of Article 1, Article 1 cites Article 2. 
# NOTE: Will only work in fields where full, unabbreviated titles are used in reference/bibliography citation format. 
# NOTE: Will have high error rate if titles are very short or comprised of common words (e.g., paper  Vulnerability  produced many false positives). Some errors result from authors using a shortened version of a title (e.g., only text before a colon) or incorrect citations or typos. Citation networks produced are therefore approximate and to be used primarily for exploration of the data.
# NOTE: Error rate may be reduced by using only reference sections of the articles of interest, rather than full texts, but this will increase work required to prepare articles. 


# ==> FIVE STEPS TO CITATION NETWORK

# STEP 1. FORMAT INPUT
# a. Papers: Folder of papers in txt format (UTF-8) organized *in SAME ORDER* as Titles 
# b. Titles: Column of paper titles in csv spreadsheet (Column #1) *in SAME ORDER* as documents in Papers folder. Need a header cell or top title will be removed.
# Recommend naming all texts in Papers folder using author last name listed alphabetically. Organize Titles using same order.


# STEP 2.  PREP
# set working directory
setwd( C:\[name of working space] ) # make sure \ not / in name
setwd( C:/Users/User/OneDrive/Adaptive Capacity Text Mining/Citation Network Test/CitationNetwork Test Data )
# load packages
install.packages(c( tm , plyr ))
library(tm)
library(plyr)


# STEP 3. LOAD INPUTS
# a. Papers 
papers<-Corpus(DirSource( [name of folder where papers located] ))
papers<-Corpus(DirSource( Papers ))
# b. Titles
titletable<-read.csv( [name of titles file].csv ) #make sure column has a header
titletable<-read.csv( TestTitles.csv )
titles<-as.vector(titletable[,1])
# load functions at bottom of this script (below Step 5)

length(papers)
length(titles)

# STEP 4. RUN FUNCTION 

CitationNetwork<-CreateCitationNetwork(papers,titles)
# add date
currentDate <- Sys.Date()
csvFileName <- paste( CitationEdges ,currentDate, .csv ,sep=  )
# save results
write.csv(CitationNetwork, file=csvFileName) 

  
# STEP 5. VISUALIZE NETWORK

# Install Gephi or other network visualization software and load CitationEdges.csv 
# Load list of titles or other spreadsheet as nodes to visualize network 
# Gephi available at https://gephi.org/


# ===> FUNCTIONS TO LOAD 

CreateCitationNetwork<-function(papers,titles){
  # prep papers corpus
  papers<-tm_map(papers, content_transformer(tolower))
  papers<-tm_map(papers, removePunctuation)
  papers<-tm_map(papers, removeNumbers)
  papers<-tm_map(papers, stripWhitespace)
  # prep titles 
  titles<-removePunctuation(titles)
  titles<-stripWhitespace(titles)
  titles<-tolower(titles)
  # create citation true/false matrix
  Cites.TF<-CiteMatrix(titles, papers)
  # format matrix into edges file 
  CitationEdges<-EdgesFormat(Cites.TF, titles)
  return(CitationEdges)
}  

# format true/false matrix into edges file 
EdgesFormat<-function(Cites.TF, titles){
  #create an empty object to put information in
  edges<-data.frame(matrix(NA), nrow=NA, ncol=NA)
  colnames(edges)<- c( Source , Target , Weight )
  for (i in 1:length(Cites.TF)){
  #for each document, run through all titles accross columns
    for (j in 1:ncol(Cites.TF)){
      # for each title, see if document [row] cited that title [column]
      if (Cites.TF[i,j]==TRUE){  #if document is cited
        temp<-data.frame(matrix(NA), nrow=NA, ncol=NA)
        colnames(temp)<- c( Source , Target , Weight )
        # first column <- document doing the citing 
        temp[1,1]<-titles[i]
        # second column <- document being cited
        temp[1,2]<-titles[j]
        # third column the yes/no [weight]
        temp[1,3]<-1  
        temp[1,4]<- Directed 
        edges<-rbind(edges,temp)    
      } 
    }
  }  
  return(edges[-1,]) #-1 removes initial row of null values
}

# Citation true/false matrix 
CiteMatrix<-function(search.vector, Ref.corpus){
  # Creates a csv matrix with True/False for citation patterns 
  citations<-data.frame(matrix(NA, nrow = length(Ref.corpus), ncol=length(search.vector)))
  #Columns are the document being cited
  colnames(citations)<-search.vector
  #Rows are the document doing the citing 
  rownames(citations)<-search.vector
  for (i in 1:length(search.vector)){
    searchi<-search.vector[i]
    papercite<-grepl(searchi, Ref.corpus$content, fixed=TRUE)
    citations[,i]<-papercite
  }
  return(citations)
}
```



- The application of methods of social network analysis in bibliometrics and webometrics. Measures and tools

https://www.researchgate.net/publication/327817518_The_application_of_methods_of_social_network_analysis_in_bibliometrics_and_webometrics_Measures_and_tools



# ScientoMiner ICR

https://zenodo.org/record/1432557#.XItjfxO2k1J



# onodo

https://onodo.org/dashboard

https://onodo.org/tutorials




# BibExcel

https://homepage.univie.ac.at/juan.gorraiz/bibexcel/



# Scientometric Portal

https://sites.google.com/site/hjamali/scientometric-portal



# leydesdorff

https://www.leydesdorff.net/software.htm




# Publish or Perish

https://harzing.com/resources/publish-or-perish



# Pajek: analysis and visualization of large networks

http://mrvar.fdv.uni-lj.si/pajek/