{"id":3452,"date":"2019-06-21T18:06:15","date_gmt":"2019-06-21T18:06:15","guid":{"rendered":"https:\/\/notebooks.dataone.org\/?p=3452"},"modified":"2019-06-21T18:18:41","modified_gmt":"2019-06-21T18:18:41","slug":"week-5-bibliometrics-preliminary-results","status":"publish","type":"post","link":"https:\/\/notebooks.dataone.org\/citation-dataone\/week-5-bibliometrics-preliminary-results\/","title":{"rendered":"Week 5- Bibliometrics & Preliminary Results"},"content":{"rendered":"\n

Happy Friday!<\/p>\n\n\n\n

I started out this week with a bit of a setback. I began linking the database I created containing all the articles produced by those affiliated with DataONE to all the citations that cite those articles (henceforth referred to as Cited By articles). While I was doing this I noticed that the citation numbers for each article that I had manually entered last week did not match up with the DOIs. I realized this was because I sorted by range rather than column in Google Drive. When you sort by range in Google Drive’s “spreadsheets” it only sorts the content you’ve selected and doesn’t expand the sort across associated cells like Excel does. This required me to replicate all the work I did last week this week. Ugh!<\/p>\n\n\n\n

Anywho, after I fixed the citation counts for the DataONE articles I finished linking the database to the Cited By article listings. Then I started to run some preliminary bibliometrics analysis using the R package Bibliometrix<\/a>. To do this in R, I first had to upload the Bibtex files I extracted in Web of Science and Scopus and then merge them into a data frame. Once merged, I was able to run the different arguments. Here are some general recommendations when exporting files for analysis from Scopus or Web of Science:<\/p>\n\n\n\n