How information is spread in our society

both through human communications and through the complex interactions of intelligent systems

We use the concept of “information competition” to understand how information propagates in the context of various events, social pressures and technology designs. This perspective helps us understand communications and artificial intelligence (AI) systems as participants in a complex adaptive system of technologies and societies.

Areas of study for the Information Competition lab

Dynamics of information environments

Epistemology and data/technological literacy

Ephemerality and durability of information

Systemic effects of intelligent systems/AI


Online social movements

Information competition has many real-world applications

Such as studying misinformation, analyzing mass communications and understanding online social movements. By studying how information competes for niches – that is, for human attention or inclusion into AI models – researchers can gain a better understanding of how social, cultural and technological change takes place. They can also use this knowledge to create better systems that can influence and use these processes in a positive way. The ICL uses large amounts of data and computational techniques to understand how information spreads, survives and thrives, and what factors contribute to its success or failure.

Informing AI Design

One area where the concept of information competition is particularly relevant is the development and implementation of AI systems. As AI pushes to become more integrated into our daily lives, it will need to compete for attention, data and resources just like any other piece of information or technology. By applying the principles of information competition to AI, researchers can better understand how these systems will interact with human societies, cultures and technologies.

Overall, the study of information competition provides a useful framework for understanding the complex interactions between information, technology and culture. As AI continues to evolve and shape our world, this framework will become increasingly important for ensuring that these systems are developed and used in ways that benefit society as a whole.

Example projects


A visualization of co-occuring ideas present in the journal American Economic Review, from the years 1960-2010. Nodes are color-coded by decade in which the idea is most represented in the journal’s text.AERnet

Oroville Spooky

This visualization shows a retweet network of accounts tweeting on the hashtag #orovilledamn during the 2017 flooding of the Feather River near Oroville, California.  Accounts are color-coded red or blue to signal conservative or liberal political leanings, and the highlighted portion shows the influence of Russian state media on a key part of the online conversation. 

The Role of Twitter in the Occupy Protests

Three Twitter streams related to Occupy Wall Street showing volumes and spikes in response to event impacts. This graph reveals a longer-term adaptive response from the crowd: the growth over time (steadily since October, and more rapidly after January 2012) of links to Occupy organizations, suggesting a refocusing of organization around Occupy websites. This figure is from “A Model of Crowd-Enabled Organization: Theory and Methods for Understanding the Role of Twitter in the Occupy Protests”.