Microdynamics of Influence in Social Systems

When algorithms steer the course

The aim of this project is to gain an understanding of how information is spread and influences people on social networks. Viral processes on social networks influence our opinions, what we buy, and which politicians we vote for, and companies such as Facebook and Google use complex algorithms to 'nudge' us to follow their recommendations.

As this algorithm-driven influence on society becomes more widespread, it becomes increasingly important for citizens, governments, consumers and businesses to understand how social network control works. One might think that these social dissemination processes are similar to the spread of diseases (epidemics), which we know a lot about, but an important difference is that social 'infection' in this case is likely to depend on the structure of the social network.

The main aim of the Microdynamics of Influence in Social Systems project is to gain an experimentally-based understanding of how social transmission mechanisms differ from the simple disease transmission of epidemics, and through our work on the Social Fabric project we have developed the technology to measure social transmission processes on a large scale.

Insight into these mechanisms can be used to reinforce positive behaviour (e.g. exercise, safe sex, sustainability) or limit negative behaviour (e.g. smoking, poor diet or intolerance), but they can also potentially be abused. Gaining more insight into these viral processes will enable us, as a society, to make informed decisions about these technological developments.

The project is headed by associate professor Sune Lehmann Jørgensen, The Technical University of Denmark.