Forage: Understanding RAG-based Sensemaking for Community Conversations
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3706599.3719756.pdf
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1.7 MB
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Adobe PDF
Checksum (MD5)
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Author(s)
Schroeder, Hope
Beeferman, Doug
Detwiller, Maya
Dimitrakopoulou, Dimitra
Roy, Deb
Date Issued
April 25, 2025
Publisher
ACM|Extended Abstracts of the CHI Conference on Human Factors in Computing Systems
Citation
Hope Schroeder, Doug Beeferman, Maya Detwiller, Dimitra Dimitrakopoulou, and Deb Roy. 2025. Forage: Understanding RAG-based Sensemaking for Community Conversations. In Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA '25). Association for Computing Machinery, New York, NY, USA, Article 283, 1–12.
Version
Final published version
Abstract
We introduce Forage, a RAG-based and LLM-augmented search engine, which we apply to the problem of sensemaking for community conversation data. We report on formative user studies introducing Forage to two distinct user groups: NPR journalists and municipal staff in the city of Durham, North Carolina. We taxonomize the query types users make with the tool, use cases that include synthesizing insights across conversations and finding content about a particular subject. We find that users tend to gravitate towards using the system for synthesis more than for pure search. We report on challenges and opportunities surfaced by performing sensemaking with an open-ended interface like Forage, such as the benefits of finding content quickly, but also the challenges users face interacting with a system in natural language. Insights from this formative study confirm the usefulness of Forage for sensemaking, but also make follow-up work, such as systematically evaluating system performance and developing appropriate design, urgent.
Description
CHI EA ’25, Yokohama, Japan
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1145/3706599.3719756
