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.
Social media users share charts and graphs — often with the same underlying data — to advocate opposing approaches to the pandemic.
Expert in social data processing proposes adjusting newsfeed algorithms to better mimic real-life interactions.
Twitter experiment shows clear self-selection into social media “echo chambers” due to political preferences.
The cross-campus effort will design human-machine systems that improve communication across divides and increase opportunity for underheard communities.
MLK Visiting Professor in Women’s and Gender Studies and scholar of critical race, feminist, and disability studies discusses misogynoir, social media, and her work at MIT this year.
Graduate student Manon Revel uses quantitative methodologies to investigate how advertising in online publications affects trust in journalism.
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.
Textual analysis of social media posts finds users’ anxiety and suicide-risk levels are rising, among other negative trends.
Series paints a holistic picture of summer youth employment programs and how research helps strengthen them.
MIT political scientist explains the responsibilities leaders have for shaping and sharing factual, truthful information in the nation's political discourse.
Several of the winning innovations apply artificial intelligence to solutions for challenges to national security.
MIT Professor Sinan Aral’s new book, “The Hype Machine,” explores the perils and promise of social media in a time of discord.
DUSP alumni Rushil Palavajjhala and Jacob Kohn empower vulnerable workers using social entrepreneurial and technical skills gained at MIT.
Teaching community organizers via WhatsApp yields encouraging results in South Africa, according to MIT Governance Lab research.
Machine learning system from MIT CSAIL can look at chest X-rays to diagnose pneumonia — and also knows when to defer to a radiologist.