The DUB Shorts format focuses on sharing a research paper in a 15 to 20-minute talk, similar to traditional conference presentations of a paper. Speakers will first present the paper, then participate in Q&A.
DUB shorts will be conducted using Zoom, via an invitation distributed to the DUB mailing list. Participants who are logged into Zoom using a UW account will be directly admitted, and participants who are not logged in to a UW account will be admitted using a Zoom waiting room.
Speakers interested in presenting a DUB Short should submit our form:
Computer Science & Engineering
Fake News on Facebook and Twitter: Investigating How People (Don’t) Investigate
With misinformation proliferating online and more people getting news from social media, it is crucial to understand how people assess and interact with low-credibility posts. This study explores how users react to fake news posts on their Facebook or Twitter feeds, as if posted by someone they follow. We conducted semi-structured interviews with 25 participants who use social media regularly for news, temporarily caused fake news to appear in their feeds with a browser extension unbeknownst to them, and observed as they walked us through their feeds. We found various reasons why people do not investigate low-credibility posts, including taking trusted posters’ content at face value, as well as not wanting to spend the extra time. We also document people’s investigative methods for determining credibility using both platform affordances and their own ad-hoc strategies. Based on our findings, we present design recommendations for supporting users when investigating low-credibility posts.
Electrical Engineering
https://momona-yamagami.github.io/
Decoding Intent With Control Theory: Comparing Muscle Versus Manual Interface Performance
Manual device interaction requires precise coordination which may be difficult for users with motor impairments. Muscle interfaces provide alternative interaction methods that may enhance performance, but have not yet been evaluated for simple (e.g., mouse tracking) and complex (e.g., driving) continuous tasks. Control theory enables us to probe continuous task performance by separating user input into intent and error correction to quantify how motor impairments impact device interaction. We compared the effectiveness of a manual versus a muscle interface for eleven users without and three users with motor impairments performing continuous tasks. Both user groups preferred and performed better with the muscle versus the manual interface for the complex continuous task. These results suggest muscle interfaces and algorithms that can detect and augment user intent may be especially useful for future design of interfaces for continuous tasks.