Slowed canonical progress in large fields of science

Examining billions of citations among nearly a hundred million papers across all fields, we find a deluge of papers leads to a slowing of ideas and the ossification of canon.

Flat teams drive scientific innovation

Teams are the engines of modern science, having grown in prevalence and size across all areas of scientific and scholarly investigation.

Prediction of robust scientific facts from literature

Here we demonstrate a Bayesian calculus that enables positive prediction of robust scientific claims with findings extracted from published literature, weighted by scientific, social and institutional factors demonstrated to increase replicability.

The Wisdom of Polarized Crowds

Study of more than 200,000 Wikipedia pages finds that collaborations which bridge the political spectrum produce higher quality work.

Large teams develop and small teams disrupt science and technology

We analyzed teamwork from more than 65 million papers, patents and software products over 100 years.

Skill discrepancies between research, education, and jobs reveal the critical need to supply soft skills for the data economy

Here we analyze and visualize the dynamic skill (mis-)alignment between academia, industry and educational offerings.

Event-level prediction of urban crime reveals a signature of enforcement bias in US cities

Here we show that, while predictive models may enhance state power through criminal surveillance, they also enable surveillance of the state by tracing systemic biases in crime enforcement.

The explosion of digital information offers an unprecedented opportunity to study the dynamics that shape human understanding, investigation and certainty. Our researchers are developing new Big Data, machine learning and crowd-sourcing approaches and techniques to:

  • Efficiently harvest and share knowledge and judgment from experts, people, articles, preprints, software, patient records, artifacts, videos and sensors

  • Learn how knowledge is made, used, certified and forgotten

  • Represent, recombine and generate knowledge in powerful ways

  • Improve knowledge generation, representation, management and innovation practices…

    …everywhere.

NEWS

Culture by Design Podcast: Surfing the Boundaries of Order and Chaos with James Evans

This week on Culture by Design, Timothy R. Clark is joined by James Evans, Director of Knowledge Lab at the University of Chicago. They talk about how to activate diversity, how to harness collective intelligence, and the paradoxical interplay between innovation and execution.

Links to the episode:
-Listen on our website

Slowed canonical progress in large fields of science

Examining billions of citations among nearly a hundred million papers across all fields, we find a deluge of papers leads to a slowing of ideas and the ossification of canon.

Pros and Cons of casting Web of Science into a graph database

Should you choose a graph database over a MySQL counterpart for your dataset of interest? How to cast your dataset into a graph schema?

James Evans on Social Computing and Diversity by Design

Listen to Complexity, at the Santa Fe Institute for a conversation with James Evans on Social computing and diversity by Design

Journal of Social Computing Launch

Launch of new IEEE journal: the Journal of Social Computing (jOsOcO)

Knowledge Lab team wins the IRIS Researcher Award

Prof. James Evans, Brendan Chambers and Donghyun Kang were awarded the IRIS Researcher Award for 2020-2021

Analysis of Wikipedia finds politically polarized teams produce better work

The Knowledge Lab analyzed more than 200,000 Wikipedia pages

Bigger teams aren’t always better in science and tech

Analysis of 65 million projects finds smaller teams produce more innovative research