Researchers need to keep up with immense literatures, though it is time-consuming and difficult to do so. In this paper, we investigate the role that intelligent interfaces can play in helping researchers skim papers, that is, rapidly reviewing a paper to attain a cursory understanding of its contents. After conducting formative interviews and a design probe, we suggest that skimming aids should aim to thread the needle of highlighting content that is simultaneously diverse, evenly-distributed, and important. We introduce Scim, a novel intelligent skimming interface that reifies this aim, designed to support the skimming process by highlighting salient paper contents to direct a skimmer's focus. Key to the design is that the highlights are faceted by content type, evenly-distributed across a paper, with a density configurable by readers at both the global and local level. We evaluate Scim with an in-lab usability study and deployment study, revealing how skimming aids can support readers throughout the skimming experience and yielding design considerations and tensions for the design of future intelligent skimming tools.
@article{arxiv.2205.04561,
title = {Scim: Intelligent Skimming Support for Scientific Papers},
author = {Raymond Fok and Hita Kambhamettu and Luca Soldaini and Jonathan Bragg and Kyle Lo and Andrew Head and Marti A. Hearst and Daniel S. Weld},
journal= {arXiv preprint arXiv:2205.04561},
year = {2023}
}
Comments
Updated to reflect version published in proceedings of IUI 2023