ForSense: Accelerating Online Research Through Sensemaking Integration and Machine Research Support

Author:

Ramos Gonzalo1ORCID,Rachatasumrit Napol2ORCID,Suh Jina1ORCID,Ng Rachel1ORCID,Meek Christopher1ORCID

Affiliation:

1. Microsoft Research, USA

2. Carnegie Mellon University, USA

Abstract

Online research is a frequent and important activity people perform on the Internet, yet current support for this task is basic, fragmented and not well integrated into web browser experiences. Guided by sensemaking theory, we present ForSense, a browser extension for accelerating people’s online research experience. The two primary sources of novelty of ForSense  are the integration of multiple stages of online research and providing machine assistance to the user by leveraging recent advances in neural-driven machine reading. We use ForSense  as a design probe to explore (1) the benefits of integrating multiple stages of online research, (2) the opportunities to accelerate online research using current advances in machine reading, (3) the opportunities to support online research tasks in the presence of imprecise machine suggestions, and (4) insights about the behaviors people exhibit when performing online research, the pages they visit, and the artifacts they create. Through our design probe, we observe people performing online research tasks, and see that they benefit from ForSense’s integration and machine support for online research. From the information and insights we collected, we derive and share key recommendations for designing and supporting imprecise machine assistance for research tasks.

Publisher

Association for Computing Machinery (ACM)

Subject

Artificial Intelligence,Human-Computer Interaction

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2. Sensecape: Enabling Multilevel Exploration and Sensemaking with Large Language Models;Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology;2023-10-29

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