It would be great if the psjournals app included information on turnaround times and acceptance rates in political science journals. This is one of the most common requests that I receive from its users, and I could not agree more.
These statistics are unfortunately unavailable for many journals.
The ones published by Taylor & Francis are now a welcome exception. The publisher has recently started to provide statistics on journal turnaround times and acceptance rates on its website — in separate sections for individual journals.
Together with Lucy Kinski, we are organising a new online seminar series on political representation: 𝙍𝙚:𝗣𝗿𝗲𝘀𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻𝘀!
The series aspires to facilitate an inclusive, supportive, and dynamic environment in which scholarly work on anything related to representation can be presented and discussed.
Each online seminar will consist of a 30-minute presentation, followed by meaningful opportunities for the audience to be involved in the discussion.
You can propose a presentation and register for events on the website of the series.
I am currently revising the slides for the next iteration of my workshop on writing reproducible research papers with R Markdown. It will take place at Campus Luzern, over two full days, in November 2020.
With over 200 slides in the presentation, I thought it is now time to introduce some internal links to facilitate the navigation across the different parts of the presentation, which is written with xaringan.
The linking syntax in R Markdown will not work here in xaringan presentations as we need to identify the target slides with the name argument.
This post introduces LikeWise — a Shiny app that retrieves and filters users’ likes on Twitter. If you are looking for a quick direction, click here for the app.
I use Twitter likes as bookmarks, but then struggle to find the one that I need among them all. Hence I have built an app. It is live at https://resulumit.shinyapps.io/likewise/. It can be used here as well, in the window below.
This post introduces psjournals — a new dataset on political science journals as well as an R package and a Shiny app that accompany the dataset. If you are looking for quick directions, click here for the package, here for the app.
Some might find this dataset useful for teaching, if not for research. However, many are likely to use psjournals for selection purposes — to see where they can submit their manuscript for consideration.
Click here for the slides, and here for all the workshop materials.
My writing workflow has been based on R Markdown for some time. In March 2020, I organised a full-day workshop at Campus Luzern, to share my experience with researchers from the three universities in the Swiss Canton of Lucerne. It went very well.
Since then I have revised the workshop material, which you can find at GitHub. The slides are better viewed here on my website.
This blogpost has led to an app that filters data on political science journals, including the journal indexes covered here. Try it out at https://resulumit.shinyapps.io/psjournals.
Here is a list of all political science journals in the Social Science Citations Index (SSCI),* ranked according to their h5-index on Google Scholar.
Google Scholar provides a similar list of top journals in political science, but this includes only the top 20 journals. I was wondering how the list looked below this number.
I have created a list of open access journals in political science—journals that make all of their articles freely accessible without delay.
Please bear in mind that this is not an exhaustive list and that editorial policies change. If you notice that one or more journals are missing or that one or more existing entries need updating, please send me an email. I would be happy to hear from you.
This blogpost has led to an app that filters data on political science journals, including article types. Try it out at https://resulumit.shinyapps.io/psjournals.
In addition to ‘regular’ articles, some political science journals publish shorter manuscripts as well. They are often called research notes, but the name, and indeed the format itself, can differ from one journal to another. Yet, this definition, by Public Opinion Quarterly, covers a lot of common ground:
The survey package is one of my favourites in R.
Among its many other uses, it can compute summary statistics by subgroups. For example, if you have a survey of individuals from several countries with an item on the respondents’ income, you can calculate the average income in each subgroup with the svyby() function.
However, like many other functions in the package, svyby() returns standard errors—but not standard deviations—of the mean values.