3 Questions: How to prove humanity online
AI agents could soon become indistinguishable from humans online. Could “personhood credentials” protect people against digital imposters?
New tool empowers users to fight online misinformation
The Trustnet browser extension lets individuals assess the accuracy of any content on any website.
For more open and equitable public discussions on social media, try “meronymity”
A communication system whose users reveal only a few verified aspects of their identity can empower less confident participants to speak up, researchers report.
Characterizing social networks
A new method to measure homophily in large group interactions offers insights into how groups might interact in the future.
Finding solidarity in the teachers’ lounge
MIT PhD candidate Elizabeth Parker-Magyar finds close workplace networks among educators drive their activism even outside of democracies.
Advancing social studies at MIT Sloan
Associate Professor Dean Eckles studies how our social networks affect our behavior and shape our lives.
Empowering social media users to assess content helps fight misinformation
An experimental platform that puts moderation in the hands of its users shows that people do evaluate posts effectively and share their assessments with others.
Frequent encounters build familiarity
PhD student Paige Bollen finds urban street networks that encourage encounters among strangers link to lower ethnic tensions and anti-immigrant hostility.
Systems scientists find clues to why false news snowballs on social media
A new model shows that the more polarized and hyperconnected a social network is, the more likely misinformation will spread.
Lincoln Laboratory convenes top network scientists for Graph Exploitation Symposium
Researchers share progress applying network science to disinformation tracing, Covid-19 modeling, and machine learning.
Turning technology against human traffickers
Lincoln Laboratory connects counter–human trafficking community in pursuit of technology to help investigate cases.
When more Covid-19 data doesn’t equal more understanding
Social media users share charts and graphs — often with the same underlying data — to advocate opposing approaches to the pandemic.
3 Questions: Devavrat Shah on curbing online misinformation
Expert in social data processing proposes adjusting newsfeed algorithms to better mimic real-life interactions.
How shared partisanship leads to social media connections
Twitter experiment shows clear self-selection into social media “echo chambers” due to political preferences.
Inequality across networks
Eaman Jahani examines how resources are distributed across networks as a social and engineering systems PhD student at the Institute for Data, Systems, and Society.