Why should someone be interested in analyzing her/his literature database? Actually, there are several good reasons to do so. You may also be interested, if you ask yourself one of the following questions:
- Which journals should your local librarian add to the university bookshelves?
- To which journal you should send you next ground-breaking manuscript?
- Which journals are most interesting for me and should get an e-mail alert?
In all these instances, you want to find some data driven recommendations and answers. Here is how you can achieve this goal with just a few lines of R syntax. Before starting your R console you only have to export your library/folder/selected entries to a csv-file.
library(plyr) setwd("c:/Dropbox/workspace/Bibliothek") ebf.bib <- read.csv("ebf-jp.csv", encoding="UTF-8") # my ebf-jp library ebf.jour.freq <- count(ebf.bib[ebf.bib$Item.Type=="journalArticle" & as.Date(substring(ebf.bib$Date.Added,1,10)) - as.Date("2014-08-03") > 1, ], "Publication.Title") ebf.jour <- subset(ebf.jour.freq, freq > 10) arrange(ebf.jour, freq, decreasing = TRUE)
In case you are interest what the output looks like. Here are the results of my last year reading:
|2||Journal of Educational Psychology||27|
|3||Learning and Individual Differences||27|
|4||Zeitschrift für Pädagogische Psychologie||19|
|5||International Journal of Science Education||12|
|7||Learning and Instruction||11|
If you have any recommendations or examples, then drop me a line in the comment box below.