Social Networks, Online Communities, and Social Media
Understanding the risks, impacts, motivators, and benefits of online information sharing.
Research Projects
Detecting and Mapping War-induced Damage to Agricultural Fields in Ukraine using Multi-Modal Remote Sensing Data
Principal Investigator(s): Sergii Skakun
Funder: NASA - Proposal Only Other Federal
Research Areas: Data Science, Analytics, and Visualization > Human-Computer Interaction > Machine Learning, AI, Computational Linguistics, and Information Retrieval > Smart Cities and Connected Communities > Social Networks, Online Communities, and Social Media
Principal Investigator(s): Sergii Skakun
Funder: NASA - Proposal Only Other Federal
Research Areas: Data Science, Analytics, and Visualization > Human-Computer Interaction > Machine Learning, AI, Computational Linguistics, and Information Retrieval > Smart Cities and Connected Communities > Social Networks, Online Communities, and Social Media
DASS: Learning Code(s): Community-Centered Design of Automated Content Moderation
Principal Investigator(s): Katie Shilton
Funder: National Science Foundation
Research Areas: Accessibility and Inclusive Design > Machine Learning, AI, Computational Linguistics, and Information Retrieval > Social Networks, Online Communities, and Social Media
Principal Investigator(s): Katie Shilton
Funder: National Science Foundation
Research Areas: Accessibility and Inclusive Design > Machine Learning, AI, Computational Linguistics, and Information Retrieval > Social Networks, Online Communities, and Social Media
Reducing the gender gap in AfD discussions: an evidence scoring approach
Principal Investigator(s): Giovanni Luca Ciampaglia
Funder: Wikimedia Foundation Other Non-Federal
Research Areas: Data Science, Analytics, and Visualization > Social Networks, Online Communities, and Social Media
Principal Investigator(s): Giovanni Luca Ciampaglia
Funder: Wikimedia Foundation Other Non-Federal
Research Areas: Data Science, Analytics, and Visualization > Social Networks, Online Communities, and Social Media
Faculty
Recent News
New UMD research found that even when prompts using generative artificial intelligence lean toward positive emotion, such as joy or excitement, the images generated from these prompts tend to evoke fear as the dominant emotion. Illustration by Adobe Stock.
Maryland Today: How Images Reflect AI’s Dark ‘Spiral’ (ft. Cody Buntain)
INFO Assistant Professor Cody Buntain explores biases in generative AI, revealing how models often produce more negative content
Photo licensed by Adobe Stock
Using AI and Visual Media to Help the U.S. Military’s Counter-Influence Campaigns
A new grant led by INFO Assistant Professor Cody Buntain boosts the U.S. military’s strategic messaging
Photo licensed by Adobe Stock