A Deixis-Centered Approach for Documenting Remote Synchronous Communication around Data Visualizations
Chang Han, Katherine E. Isaacs

TL;DR
This paper presents a novel framework for documenting remote data analysis meetings by capturing cursor gestures and audio, converting them into interactive documents, and leveraging language models for context-aware annotations, improving over traditional transcripts.
Contribution
The paper introduces a new method that treats deixis as a core element, integrating cursor gestures and language models to create interactive, context-rich documentation of data meetings.
Findings
Participants preferred automated interactive documents over recordings and transcripts.
The framework effectively captures cursor-based deictic gestures.
A preliminary taxonomy of cursor-based deixis was developed.
Abstract
Referential gestures, or as termed in linguistics, deixis, are an essential part of communication around data visualizations. Despite their importance, such gestures are often overlooked when documenting data analysis meetings. Transcripts, for instance, fail to capture gestures, and video recordings may not adequately capture or emphasize them. We introduce a novel method for documenting collaborative data meetings that treats deixis as a first-class citizen. Our proposed framework captures cursor-based gestural data along with audio and converts them into interactive documents. The framework leverages a large language model to identify word correspondences with gestures. These identified references are used to create context-based annotations in the resulting interactive document. We assess the effectiveness of our proposed method through a user study, finding that participants…
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Taxonomy
TopicsDistributed and Parallel Computing Systems · Multimedia Communication and Technology · Data Visualization and Analytics
