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Does somebody know how can you do some data mining of your Bibtex database? For example, some statistics about the number of papers per journal, author or year; stuff like that. Is there a tool or a website available?

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6

I don't know of such a tool, but it should be possible to process BibTeX data in statistical software (such as R) or even in Excel.

The bibtex package on CRAN can parse BibTeX files. Converting to a data frame should be possible on an attribute-by-attribute basis. Then you can analyze whatever you want. See also this related question on SO.

> rref <- read.bib()
> rref
R Development Core Team (2009). _R: A Language and Environment for
Statistical Computing_. R Foundation for Statistical Computing, Vienna,
Austria. ISBN 3-900051-07-0, <URL: http://www.R-project.org>.
> str(rref)
List of 1
 $ :Class 'bibentry'  hidden list of 1
  ..$ :List of 7
  .. ..$ title       : chr "R: A Language and Environment for Statistical Computing"
  .. ..$ author      :Class 'person'  hidden list of 1
  .. .. ..$ :List of 5
  .. .. .. ..$ given  : chr "R Development Core Team"
  .. .. .. ..$ family : NULL
  .. .. .. ..$ role   : NULL
  .. .. .. ..$ email  : NULL
  .. .. .. ..$ comment: NULL
  .. ..$ organization: chr "R Foundation for Statistical Computing"
  .. ..$ address     : chr "Vienna, Austria"
  .. ..$ year        : chr "2009"
  .. ..$ note        : chr "{ISBN} 3-900051-07-0"
  .. ..$ url         : chr "http://www.R-project.org"
  .. ..- attr(*, "bibtype")= chr "Manual"
  .. ..- attr(*, "key")= chr "R"
 - attr(*, "class")= chr "bibentry"
 - attr(*, "strings")= Named chr(0) 
  ..- attr(*, "names")= chr(0) 
> rref$url
[1] "http://www.R-project.org"

If you prefer Excel, you might want to convert your bib file to XML first. I haven't tried that, though.

3

This question is about bibliometrics.

bibliometrix is an R package that incorporates several methods for such analysis. From their introduction vignette:

bibliometrix package provides a set of tools for quantitative research in bibliometrics and scientometrics.

Bibliometrics turns the main tool of science, quantitative analysis, on itself. Essentially, bibliometrics is the application of quantitative analysis and statistics to publications such as journal articles and their accompanying citation counts. Quantitative evaluation of publication and citation data is now used in almost all scientific fields to evaluate growth, maturity, leading authors, conceptual and intellectual maps, trends of a scientific community.

Bibliometrics is also used in research performance evaluation, especially in university and government labs, and also by policymakers, research directors and administrators, information specialists and librarians, and scholars themselves.

bibliometrix supports scholars in three key phases of analysis:

  • Data importing and conversion to R format;

  • Bibliometric analysis of a publication dataset;

  • Building matrices for co-citation, coupling, collaboration, and co-word analysis. Matrices are the input data for performing network analysis, multiple correspondence analysis, and any other data reduction techniques.

Installation

install.packages(“bibliometrix”, dependencies=TRUE)

Example

Taken from the vignette:

file <- "https://www.bibliometrix.org/datasets/savedrecs.bib"

M <- convert2df(file = file, dbsource = "isi", format = "bibtex")

results <- biblioAnalysis(M, sep = ";")

S <- summary(object = results, k = 10, pause = FALSE)

This yields the information that OP asked and more:

For example, some statistics about the number of papers per journal,

## Most Relevant Sources
## 
##                                                            Sources        Articles
## 1  SCIENTOMETRICS                                                               49
## 2  JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY       14
## 3  JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE                       8
## 4  JOURNAL OF DOCUMENTATION                                                      6
## 5  JOURNAL OF INFORMATION SCIENCE                                                6
## 6  JOURNAL OF INFORMETRICS                                                       6
## 7  BRITISH JOURNAL OF ANAESTHESIA                                                5
## 8  LIBRI                                                                         5
## 9  SOCIAL WORK IN HEALTH CARE                                                    5
## 10 TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE                                   5

Note that this is only displaying the top 10 journals, as defined by the k argument in the call to summary(). Similarly, only the top 10 authors are listed below.

author

## Most Productive Authors
## 
##    Authors        Articles Authors        Articles Fractionalized
## 1     BORNMANN L         8     BORNMANN L                    4.67
## 2     KOSTOFF RN         8     WHITE HD                      3.50
## 3     MARX W             6     MARX W                        3.17
## 4     HUMENIK JA         5     ATKINSON R                    3.00
## 5     ABRAMO G           4     BROADUS RN                    3.00
## 6     D'ANGELO CA        4     CRONIN B                      3.00
## 7     GARG KC            4     BORGMAN CL                    2.50
## 8     GLANZEL W          4     MCCAIN KW                     2.50
## 9     WHITE HD           4     PERITZ BC                     2.50
## 10    ATKINSON R         3     KOSTOFF RN                    2.10

or year

## Annual Scientific Production
## 
##  Year    Articles
##     1985        4
##     1986        3
##     1987        6
##     1988        7
##     1989        8
##     1990        6
##     1991        7
##     1992        6
##     1993        5
##     1994        7
##     1995        1
##     1996        8
##     1997        4
##     1998        5
##     1999        2
##     2000        7
##     2001        8
##     2002        5
##     2003        1
##     2004        3
##     2005       12
##     2006        5
##     2007        5
##     2008        8
##     2009       14
##     2010       17
##     2011       20
##     2012       25
##     2013       21
##     2014       29
##     2015       32
## 
## Annual Percentage Growth Rate 7.177346 

Caveat

This package assumes the .bib file (or other format) comes from a specified source: the dbsource argument in the call to convert2df(). If you already have an existing bib file from somewhere else, some analysis might not work well. From their FAQ:

Q5 - I want to load a bibtex file created by a reference manager software but when I run the function convert2df it returns an error:

Error in seq.default(iStart, iStop) : 'from' must be a finite number

The problem is the data format.

Unfortunately, bibtex is not a proper standardized format, so it could change when created from different sources.

Bibliometrix/biblioshiny need a bibtex file formatted exactly as exported by WoS or Scopus and with the full set of mandatory metadata (authors' name, affiliations, references, etc.). If not, it will not work.

I use Mendeley to generate my bib files. I tried the example above with a few different bib files, and it was able to generate similar outputs, even though it throws a warning:

> bib <- '/path/to/my/bibfile.bib'
> bibdf <- convert2df(file = bib, dbsource = 'isi', format = 'bibtex')

Converting your isi 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://cran.r-project.org/web/packages/bibliometrix/vignettes/Data-Importing-and-Converting.html)
- 'A brief introduction to bibliometrix' (https://cran.r-project.org/web/packages/bibliometrix/vignettes/bibliometrix-vignette.html)


Missing fields:  ID C1 CRDone!

I would also recommend going through the Data Importing and Converting vignette in the warning message.

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