One of the joys of posting a preprint is seeing that people are viewing, downloading and (hopefully) reading your paper. On bioRxiv you can check out the statistics for your paper in the metrics tab. We posted a preprint recently and it clocked up over 1,000 views in the first day or so. This made […]
Tag: metrics
Prehistoric: when do authors preprint their papers?
Previously, I took advantage of a dataset that linked preprints to their published counterparts to look at the fraction of papers in a journal that are preprinted. This linkage can be used to answer other interesting questions. Such as: when do authors preprint their papers relative to submission? And does this differ by journal? There’s […]
All The Right Friends II: clustering papers using Google Scholar data
In a previous post, I looked at how Google Scholar ranks co-authors. While I had the data available I wondered whether paper authorship could be used in other ways. A few months back, John Cook posted about using Jaccard index and jazz albums. The idea is to look at the players on two jazz albums […]
All The Right Friends: how does Google Scholar rank co-authors?
On a scientist’s Google Scholar page, there is a list of co-authors in the sidebar. I’ve often wondered how Google determines in what order these co-authors appear. The list of co-authors on a primary author’s page is not exhaustive. It only lists co-authors who also have a Google Scholar profile. They also have to be […]
Yesterday’s Numbers
A quick post this week. I write “this week” in an attempt to convince regular readers that weekly posting will continue. I noticed that J. Cell Sci. give download metrics for their papers and that these downloads are categorised into abstract, full-text and PDF. I was interested in how one of my papers performed. After […]
Rollercoaster IV: ups and downs of Google Scholar citations
Time for an update to a previous post. For the past few years, I have been using an automated process to track citations to my lab’s work on Google Scholar (details of how to set this up are at the end of this post). Due to the nature of how Google Scholar tracks citations, it […]
Five Get Over Excited: Academic papers that cite quantixed posts
Anyone that maintains a website is happy that people out there are interested enough to visit. Web traffic is one thing, but I take greatest pleasure in seeing quantixed posts being cited in academic papers. I love the fact that some posts on here have been cited in the literature more than some of my […]
One With The Freaks – very highly cited papers in biology
I read this recent paper about very highly cited papers and science funding in the UK. The paper itself was not very good, but the dataset which underlies the paper is something to behold, as I’ll explain below. The idea behind the paper was to examine very highly cited papers in biomedicine with a connection […]
For What It’s Worth: Influence of our papers on our papers
This post is about a citation analysis that didn’t quite work out. I liked this blackboard project by Manuel Théry looking at the influence of each paper authored by David Pellman’s lab on the future directions of the Pellman lab. It reminds me that papers can have impact in the field while others might be […]
Rollercoaster III: yet more on Google Scholar
In a previous post I made a little R script to crunch Google Scholar data for a given scientist. The graphics were done in base R and looked a bit ropey. I thought I’d give the code a spring clean – it’s available here. The script is called ggScholar.R (rather than gScholar.R). Feel free to […]