Twitter has become a powerful medium for organizing and communicating with factions during popular uprisings: the crisis in Egypt, the uprising in Syria, the revolution in Iran, and other conflicts all around the world. Twitter's effectiveness relies on its ability for the various factions to self-organize and to fight the information battle in social media.
Esteban Moro Egido, a mathematics professor at Universidad Carlos III in Madrid, puts this battle into stark relief with a video depicting Twitter activity around Spain's general strike in March this year. Esteban has used the R language for years to understand complex networks with applications in areas such as telecommunications and social media, and has put those skills to great use analyzing all of the tweets, retweets and mentions related to the strike. Here's the video:
Each point in the animation represents a twitter user, each colour-coded according to their faction in the debate (pro-strike, anti-strike, or somewhere in between). He used community-finiding algorithms to automatically assign Twitter users to factions, and the animation itself was created entirely with R using the igraph package, and encoded to video using ffmpeg. You can create similar videos yourself for other dynamic political discussions on Twitter: Esteban has kindly provided a tutorial on how to create such animations, with R code.
Implicit None: Temporal network of information diffusion in Twitter