title: WildVis: Open Source Visualizer for Million-Scale Chat Logs in the Wild
summary: 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.
paper_authors._id: 66da5ea466e970a15f62e85f
paper_authors.name: Yuntian Deng
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paper_authors.fullname: Yuntian Deng
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paper_authors._id: 66da5ea466e970a15f62e860
paper_authors.name: Wenting Zhao
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paper_authors.fullname: Wenting Zhao
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paper_authors.user: wentingzhao
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paper_authors.name: Jack Hessel
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paper_authors.fullname: Jack Hessel
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paper_authors.user: jmhessel
paper_authors._id: 66da5ea466e970a15f62e862
paper_authors.name: Xiang Ren
paper_authors._id: 66da5ea466e970a15f62e863
paper_authors.name: Claire Cardie
paper_authors._id: 66da5ea466e970a15f62e864
paper_authors.name: Yejin Choi
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paper_authors.avatarUrl: /avatars/52e54bdd6a1fb6c774a40cd70f3d7925.svg
paper_authors.fullname: Yejin Choi
paper_authors.type: user
paper_authors.user: yejinchoinka
paper_title: WildVis: Open Source Visualizer for Million-Scale Chat Logs in the Wild
paper_summary: 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.
paper_ai_keywords: interactive tool conversation analysis search and visualization capabilities text and embedding spaces search index construction embedding precomputation and compression caching annotatebot misuse topic distributions user-specific conversation patterns