CiteSee
When reading a scholarly article, inline citations help researchers contextualize the current article and discover relevant prior work. However, it can be challenging to prioritize and make sense of the hundreds of citations encountered during literature reviews. This paper introduces CiteSee, a paper reading tool that leverages a user’s publishing, reading, and saving activities to provide personalized visual augmentations and context around citations. First, CiteSee connects the current paper to familiar contexts by surfacing known citations a user had cited or opened. Second, CiteSee helps users prioritize their exploration by highlighting relevant but unknown citations based on saving and reading history. We conducted a lab study that suggests CiteSee is significantly more effective for paper discovery than three baselines. A field deployment study shows CiteSee helps participants keep track of their explorations and leads to better situational awareness and increased paper discovery via inline citation when conducting real-world literature reviews.
Conference Presentation
Publication
🏆 Best Paper Award
CiteSee: Augmenting Citations in Scientific Papers with Persistent and Personalized Historical Context
Joseph Chee Chang, Amy X. Zhang, Jonathan Bragg, Andrew Head, Kyle Lo, Doug Downey, Daniel S. Weld. Proceedings of the CHI Conference on Human Factors in Computing Systems. 2023.
CiteSee: Augmenting Citations in Papers with Persistent and Personalized Historical Context. AI2 Blog. 2023. Joseph Chee Chang.