WildVis: Open Source Visualizer for Million-Scale Chat Logs in the Wild
Authors: name: Yuntian Deng, name: Wenting Zhao, name: Jack Hessel, name: Xiang Ren, name: Claire Cardie, name: Yejin Choi

The increasing availability of real-world conversation data offers exciting
opportunities for researchers to study user-chatbot interactions. However, the
sheer volume of this data makes manually examining individual conversations
impractical. To overcome this challenge, we introduce WildVis, an interactive
tool that enables fast, versatile, and large-scale conversation analysis.
WildVis provides search and visualization capabilities in the text and
embedding spaces based on a list of criteria. To manage million-scale datasets,
we implemented optimizations including search index construction, embedding
precomputation and compression, and caching to ensure responsive user
interactions within seconds. We demonstrate WildVis's utility through three
case studies: facilitating chatbot misuse research, visualizing and comparing
topic distributions across datasets, and characterizing user-specific
conversation patterns. WildVis is open-source and designed to be extendable,
supporting additional datasets and customized search and visualization
functionalities.