WildVis: Open Source Visualizer for Million-Scale Chat Logs in the Wild
This tool addresses the problem of impractical manual examination for researchers studying user-chatbot interactions, though it is incremental as it builds on existing visualization and search techniques.
The authors tackled the challenge of analyzing large-scale real-world conversation data by introducing WildVis, an interactive tool that enables fast and versatile analysis of million-scale chat logs, with optimizations ensuring responsive interactions within seconds.
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' 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.