ConToVi: Multi-Party Conversation Exploration using Topic-Space Views

Contributors

Abstract

We introduce a novel visual analytics approach to analyze speaker behavior patterns in multi-party conversations. We propose Topic-Space Views to track the movement of speakers across the thematic landscape of a conversation. Our tool is designed to assist political science scholars in exploring the dynamics of a conversation over time to generate and prove hypotheses about speaker interactions and behavior patterns. Moreover, we introduce a glyph-based representation for each speaker turn based on linguistic and statistical cues to abstract relevant text features. We present animated views for exploring the general behavior and interactions of speakers over time and interactive steady visualizations for the detailed analysis of a selection of speakers. Using a visual sedimentation metaphor we enable the analysts to track subtle changes in the flow of a conversation over time while keeping an overview of all past speaker turns. We evaluate our approach on real-world datasets and the results have been insightful to our domain experts.

Publications

  • M. El-Assady, V. Gold, C. Acevedo, C. Collins, and D. Keim, “ConToVi: Multi-Party Conversation Exploration using Topic-Space Views,” Computer Graphics Forum, vol. 35, iss. 3, pp. 431-440, 2016.
    [Bibtex] [PDF]
    @Article{ElA2016a,
      author =    {Mennatallah El-Assady and Valentin Gold and Carmela Acevedo and Christopher Collins and Daniel Keim},
      title =    {ConToVi: Multi-Party Conversation Exploration using Topic-Space Views},
     journal = {Computer Graphics Forum},
     volume = 35,
    number = 3,
      year =   2016,
     pages = {431-440 }
    }

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Demo

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Video

Acknowledgements

Research

EduApps – Supporting Non-Native English Speakers to Overcome Language Transfer Effects

Metatation: Annotation as Implicit Interaction to Bridge Close and Distant Reading

DataTours: A Data Narratives Framework

Perceptual Biases in Font Size as a Data Encoding

Progressive Learning of Topic Modeling Parameters: A Visual Analytics Framework

Abbreviating Text Labels on Demand

NEREx: Named-Entity Relationship Exploration in Multi-Party Conversations

ConToVi: Multi-Party Conversation Exploration using Topic-Space Views

PhysioEx: Visual Analysis of Physiological Event Streams

Using Visual Analytics of Heart Rate Variation to Aid in Diagnostics

Off-Screen Desktop

PivotSlice

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#FluxFlow: Visual Analysis of Anomalous Information Spreading on Social Media

Optimizing Hierarchical Visualizations with the Minimum Description Length Principle

Lexichrome

SentimentState: Exploring Sentiment Analysis on Twitter

Facilitating Discourse Analysis with Interactive Visualization

DimpVis

Glidgets

TandemTable

Simple Multi-Touch Toolkit

Exploring Text Entities with Descriptive Non-photorealistic Rendering

Investigating the Semantic Patterns of Passwords

Bubble Sets: Revealing Set Relations with Isocontours over Existing Visualizations

Parallel Tag Clouds to Explore Faceted Text Corpora

VisLink: Revealing Relationships Amongst Visualizations

DocuBurst: Visualizing Document Content using Language Structure

Tabletop Text Entry Techniques

Lattice Uncertainty Visualization: Understanding Machine Translation and Speech Recognition

WordNet Visualization

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