1 billion tweets or retweets were collected from Germany’s Twitter database by Daniel Thilo Schröder. These were then used to build the underlying network of acquaintances which labels what can be described as "social distance" between Twitter users.
This social distance is based on two features that can be easily grasped from the Twitter database: at what frequency two users tweet with each other and the time-span between tweets and retweets.
The researchers have introduced a framework to generate large-scale networks of social connectivity. This is openly available and can, among other things, be used as a ground basis to investigate how real and fake information spreads throughout social networks.
The people behind the paper are Daniel Thilo Schröder, Postdoctoral Fellow at Simula, Johannes Langguth, Research Scientist at Simula, Luk Burchard, PhD student at Simula, Konstantin Pogorelov, Postdoctoral Fellow at Simula, and Pedro Lind from the Department of Computer Science, OsloMet.
Read more:
- The paper The connectivity network underlying the German’s Twittersphere: a testbed for investigating information spreading phenomena (nature.com)
- the dataset Interaction Network of the German Twittersphere (simula.no)
The top picture illustrates the network of the 1 billion tweets and retweets that were collected.
