Snake, the twitterbot – an experiment in game design

snake is a procedural fable that uses judeo-christian imagery to show the dangers of unchecked growth, i.e., capitalism [@aparrish]

In this blog post, we present a port of the Snake game to Twitter. We detail some of the (twisted) game design choices we made, along with code (please follow the links) and explanations. The whole project is available on GitHub (100% R) and here is the Twitter account.
Rules are short: a snake must eat in order to grow up. Touching elements of its body or walls ends the game. There are variants for this game, an interesting one being that the longer the snake, the faster the game. We implemented this in our Snake game. Furthermore, there are also multiplayer variants of the game. That, we did not even try to implement it. Continue reading “Snake, the twitterbot – an experiment in game design”

Créer un Twitterbot avec R : le Teletext suisse sur Twitter

«C’est comme si on arrivait à enfiler un vinyle dans un lecteur MP3
[Nicolae Schiau]

Dans ce billet de blog, nous décrivons le processus de réalisation d’un Twitterbot avec R. Le code est disponible ici.

If you do not read French but are just interested by how to code a Twitterbot with R, you can find the code here.

Une page du Teletext telle qu’elle apparaît une fois postée par @TeletextCH sur Twitter.

Hackathon SSR

Étant des amateurs inconditionnels du Teletext suisse, Adrien Schnarrenberger et moi-même avons décidé de réaliser un Twitterbot postant les «breaking news» de ce média mythique lors du premier hackathon de la SSR [dead link], les 20 et 21 novembre 2015. Le résultat se trouve ici :


Continue reading “Créer un Twitterbot avec R : le Teletext suisse sur Twitter”

Visualising Networks Part 1: A Critique

This is the first post of a series on network visualisation. 

Thanks to the facilitated access to network analysis tools and the growing interest in many disciplines towards studying the relations structuring datasets, networks have become ubiquitous objects in science, in newspapers, on tech book covers, all over the Web, and to illustrate anything big data-related (hand in hand with word clouds.). Unfortunately, the resort to networks has reached a point where in a conference I heard a speaker say:

Since this is mandatory, here is a network visualisation of these data. Sorry if you cannot see anything in this big hairball.

Hairballs. [Sources 1 2 3 4]
Hairballs found via Google Images. Note that the authors of these images themselves originally called them “hairball”. [Sources 1 2 3 4]

You would expect in a conference that everything presented has a purpose. Sadly, it seems that there is underlying pressure in scientific communities to create such horrors.

A network is easy to create, easy to draw, easy to export, and usually nobody ask questions, because they are often difficult to grasp. This could be different. Continue reading “Visualising Networks Part 1: A Critique”