A citation manipulation scheme so easy, even a cat can do it.

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 run it and raise an issue or leave a comment if you have some ideas.

I’ve previously written about Google Scholar. Its usefulness and its instability. I just read a post by Jon Tennant on how to harvest Google Scholar data in R and I thought I would use his code as the basis to generate some nice plots based on Google Scholar data. A script for R is below and can be found here. Graphics are base R but do the job. First of all I took it for a spin on my own data.

What is your h-index on Twitter? This thought crossed my mind yesterday when I saw a tweet that was tagged #academicinsults It occurred to me that a Twitter account is a kind of micro-publishing platform. So what would “publication metrics” look like for Twitter? Twitter makes analytics available, so they can easily be crunched. The main metrics are impressions and engagements per tweet.

My post on the strange data underlying the new impact factor for eLife was read by many people. Thanks for the interest and for the comments and discussion that followed. I thought I should follow up on some of the issues raised in the post. To recap: eLife received a 2013 Impact Factor despite only publishing 27 papers in the last three months of the census window. Other journals, such as Biology Open did not.

When it comes to measuring the impact of our science, citations are pretty much all we have. And not only that but they only say one thing – yeah – with no context. How can we enrich citation data? Much has been written about how and why and whether or not we should use metrics for research assessment.

This post is about metrics and specifically the H-index. It will probably be the first of several on this topic. I was re-reading a blog post by Alex Bateman on his affection for the H-index as a tool for evaluating up-and-coming scientists.