Effects of Collaboration on the Performance of Interactive Theme Discovery Systems
Alvin Po-Chun Chen Parabel (Company), Rohan Das University of Colorado at Boulder, Dananjay Srinivas University of Colorado at Boulder, Alexandra Barry, Maksim Seniw Charter Communications, Maria Leonor Pacheco University of Colorado at Boulder
NLP-assisted solutions to support qualitative data analysis have gained considerable traction. However, no unified evaluation framework exists which can account for the many different settings in which qualitative researchers may employ them. In this paper, we propose a framework to evaluate the way collaboration settings may produce different research outcomes across a variety of interactive systems. Specifically, we study the impact of synchronous vs. asynchronous collaboration using three different NLP-assisted qualitative research tools and present a comprehensive analysis of the differences in the consistency, cohesiveness, and correctness of their outcomes.
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Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · 2026 · 正式发表