Skip to main content

Berlin Election Posters

For my political science readers out there, I've put together a short slide show of election poster photos I've taken recently (scroll down and click). These are for the upcoming Berlin state elections (Battle for the Rotes Rathaus). 

A few things I thought were interesting:
  • The top poster in the first photo is for current SPD mayor Klaus Wowereit. Though the SPD is a social democratic party, in Berlin it is in coalition with Die Linke ("The Left" party created from pieces of the old East German Socialist Unity Party), and this is Berlin which votes pretty strongly for left parties, they only have a small blob of red on their poster. The major colour is blue? I asked a German coworker (and a researcher for an SPD MP) about this. She explained "they chose blue because they want to look cool". Oddly, the centre-right CDU (bottom picture 3 and 5) use read for their letters, but stick to blue otherwise.

  • The second poster is for a Pirate Party candidate. I was a little confused about why Pirate party candidates would even run in a local election (they mostly care about federal-level internet regulation issues). 

  • The yellow top poster in picture 3 is for the (european-style) liberal FDP party. The main message of the poster is 'your government can do more for you than just give parking tickets'. This is an interesting appeal considering the discussion on the role of government in the US.

  • The bottom CDU poster in picture 3 is basically the Obama "Change" slogan. This is clearly an appeal to change the local government SPD-Die Linke coalition rather than Merkel's federal CDU-led government. However, I would imagine that state elections in Germany are just as much second-order elections as in other sub-national contests and the CDU will do just as badly as in other recent state elections.

  • Finally, I've always thought it was weird that US contests, which are supposed to be very candidate-centred, rarely feature campaign posters with the candidates photo, but many places where there is proportional representation and, supposedly less focus on candidates, most posters will have candidates' photos. 



Popular posts from this blog

Dropbox & R Data

I'm always looking for ways to download data from the internet into R. Though I prefer to host and access plain-text data sets (CSV is my personal favourite) from GitHub (see my short paper on the topic) sometimes it's convenient to get data stored on Dropbox . There has been a change in the way Dropbox URLs work and I just added some functionality to the repmis R package. So I though that I'ld write a quick post on how to directly download data from Dropbox into R. The download method is different depending on whether or not your plain-text data is in a Dropbox Public folder or not. Dropbox Public Folder Dropbox is trying to do away with its public folders. New users need to actively create a Public folder. Regardless, sometimes you may want to download data from one. It used to be that files in Public folders were accessible through non-secure (http) URLs. It's easy to download these into R, just use the read.table command, where the URL is the file name

Slide: one function for lag/lead variables in data frames, including time-series cross-sectional data

I often want to quickly create a lag or lead variable in an R data frame. Sometimes I also want to create the lag or lead variable for different groups in a data frame, for example, if I want to lag GDP for each country in a data frame. I've found the various R methods for doing this hard to remember and usually need to look at old blog posts . Any time we find ourselves using the same series of codes over and over, it's probably time to put them into a function. So, I added a new command– slide –to the DataCombine R package (v0.1.5). Building on the shift function TszKin Julian posted on his blog , slide allows you to slide a variable up by any time unit to create a lead or down to create a lag. It returns the lag/lead variable to a new column in your data frame. It works with both data that has one observed unit and with time-series cross-sectional data. Note: your data needs to be in ascending time order with equally spaced time increments. For example 1995, 1996

A Link Between topicmodels LDA and LDAvis

Carson Sievert and Kenny Shirley have put together the really nice LDAvis R package. It provides a Shiny-based interactive interface for exploring the output from Latent Dirichlet Allocation topic models. If you've never used it, I highly recommend checking out their XKCD example (this paper also has some nice background). LDAvis doesn't fit topic models, it just visualises the output. As such it is agnostic about what package you use to fit your LDA topic model. They have a useful example of how to use output from the lda package. I wanted to use LDAvis with output from the topicmodels package. It works really nicely with texts preprocessed using the tm package. The trick is extracting the information LDAvis requires from the model and placing it into a specifically structured JSON formatted object. To make the conversion from topicmodels output to LDAvis JSON input easier, I created a linking function called topicmodels_json_ldavis . The full function is below. To