Exploratory Visual Analysis of Transcripts for Interaction Analysis in Human-Computer Interaction

要旨

Transcripts are central to qualitative research in HCI, particularly for researchers using methods of Conversation Analysis (CA) and Interaction Analysis (IA) who study the socially situated nature of human-computer interaction. However, CA and IA researchers continue to highlight the significant need for more dynamic ways to visualize transcripts to support interaction analysis. This need is particularly evident in HCI, where transcripts as a form of data have received little attention. In this article, we make three contributions to HCI research. First, we present Transcript Explorer, an open-source visualization system that integrates three visualization techniques we have developed to interactively visualize transcripts linked to videos: Distribution Diagrams, Turn Charts and Contribution Clouds. Second, we present findings from a qualitative analysis of focus group interviews with three different qualitative research groups who engaged with this system to analyze common transcript data. Finally, we expand upon transcripts as a unique form of data for HCI research and propose directions for future research.

著者
Ben Rydal. Shapiro
Georgia State University, Atlanta, Georgia, United States
Rogers Hall
Vanderbilt University, Nashville, Tennessee, United States
Arpit Mathur
Georgia Institute of Technology, Atlanta, Georgia, United States
Edwin Zhao
Georgia State University, Atlanta, Georgia, United States
DOI

10.1145/3706598.3713490

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713490

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Make it Visible

G418+G419
6 件の発表
2025-04-30 23:10:00
2025-05-01 00:40:00
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