Race and gender bias in clinical practice is a persistent cause of healthcare disparities. This study investigates the potential of a peer network approach to reduce bias in medical treatment decisions within an experimental setting.
Errors in clinical decision-making are disturbingly common. In this study, we show that structured information–sharing networks among clinicians significantly reduce diagnostic errors, and improve treatment recommendations.
We develop an experimental study in which investors make financial forecasts before and after learning the beliefs of others in a structured social network, to explore the effects of networked collective intelligence on predictive accuracy and sentiment cascades in financial markets.
We examine the network dynamics that lead populations of individuals who initially disagree about which behaviors are virtuous to arrive at consistent, replicable consensus in their beliefs about virtuous behavior.
This study addresses a 21st century problem that arises from the interaction between the history of institutional discrimination and racism in health, and the network dynamics of how a community’s structure affects the flow of novel health information about vaccination.
The online proliferation of false, hateful, and illegal content has required social media organizations to monitor and remove content that violates their community standards – a practice known as content moderation.
How does the civility of online interactions affect the quality of democratic decision-making? Recent evidence suggests that incivility can increase participation, which is often thought of as desirable for good democracy.
To test whether the wisdom of crowds is robust to partisan bias, we conducted two web-based experiments in which individuals answered factual questions known to elicit partisan bias before and after observing the estimates of peers in a politically homogeneous social network.
In this study, we use formal models and online experiments to see how categories emerge in social networks. Specifically, we develop novel theories and analyses to explain how categories emerge in social networks of various sizes and topologies.
In an online experiment, we use engineered social networks to harness peer influence among smokers and nonsmokers in such a way that counteracts and eliminates biased interpretations of warning labels.
In this study, we provide a method for facilitating cross-party communication that eliminates biased interpretations of climate data among conservatives, while also improving the interpretations of liberals.
In a randomized controlled trial, we evaluate the effects of social support and social comparison independently, and in combination, to determine how social motivations for behavior change directly impact people’s exercise activity.
The “tipping point” is a common explanation for sudden shifts in collective behavior, but the limitations of historical evidence and conflicting theoretical models present a challenge to understanding how a small but committed group can change the behavior of an entire population.
This project seeks to understand the discussion of HPV vaccination and cervical cancer on social media. Cervical cancer causes 4,220 annual deaths. 17% women do not receive appropriate Pap smear screening.
How do online health networks evolve? A growing number of online health communities offer individuals the opportunity to receive information, advice, and support from their peers.
To understand how changes in people’s social “neighborhoods” affect the spread of health innovations, we developed an in vivo study that manipulated the level of “homophily”—similarity of social contacts—among the participants in an online fitness program.
How do norms emerge? In small groups, people have complete knowledge of one another’s behaviors, making it relatively easy to create shared expectations.
Do efficient communication networks increase collective intelligence? Scientists, engineers and strategists all work within highly connected environments where each person’s solutions are used to inspire and inform the work of others.
Decentralized networks offer enormous potential for crowd-sourced information aggregation, whether it takes the form of emergent market forces or a deliberative organizational process.
Exposure to women using a novel method of contraception has the potential to influence contraceptive beliefs, and ultimately an individual’s decision to use contraception.
Sedentary lifestyle is an escalating national and global epidemic that has commanded increasing attention from health care professionals and social scientists.
Harnessing the new opportunity offered by social media, our research pioneered the use of online technologies to investigate the effects of social structure on the spread of health behaviors.
