Reviewing the literature to understand relevant past work is a critical part of research. However, as the scientific literature grows the challenges for users to find and make sense of the many different threads of research grow as well. In this work we explore a tool integrated into users’ reading process that helps them with leveraging authors’ existing summarization of prior research threads such as in related work sections. We developed Threddy that supports efficient extraction and organization of threads along with supporting evidence as scientists read research articles. The system then recommends further relevant articles based on user-created threads. Our lab study showed that Threddy helps scientists to follow and curate research threads without breaking out of their flow of reading, collect relevant papers and clips, and discover interesting new articles to further grow threads.

Abstract

Reviewing the literature to understand relevant threads of past work is a critical part of research and vehicle for learning. However, as the scientific literature grows the challenges for users to find and make sense of the many different threads of research grow as well. Previous work has helped scholars to find and group papers with citation information or textual similarity using standalone tools or overview visualizations. Instead, in this work we explore a tool integrated into users’ reading process that helps them with leveraging authors’ existing summarization of threads, typically in introduction or related work sections, in order to situate their own work’s contributions. To explore this we developed a prototype that supports efficient extraction and organization of threads along with supporting evidence as scientists read research articles. The system then recommends further relevant articles based on user-created threads. We evaluate the system in a lab study and find that it helps scientists to follow and curate research threads without breaking out of their flow of reading, collect relevant papers and clips, and discover interesting new articles to further grow threads.

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Hyeonsu B. Kang, Joseph Chee Chang, Yongsung Kim, Aniket Kittur
"Threddy: An Interactive System for Personalized Thread-based Exploration and Organization of Scientific Literature"
In Proceedings of the 35th ACM User Interface Software and Technology Symposium: UIST 2022.

Bibtex

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@article{kang2022threddy,
 title={Threddy: An Interactive System for Personalized Thread-based Exploration and Organization of Scientific Literature},
 author={Kang, Hyeonsu B and Chang, Joseph Chee and Kim, Yongsung and Kittur, Aniket},
 booktitle = {},
 series = {UIST '22},
 year = {2022},
 location = {Bend, OR, USA},
 publisher = {ACM},
 address = {New York, NY, USA}
}