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Visualizing Email Content: Portraying Relationships From - - PowerPoint PPT Presentation

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Visualizing Email Content: Portraying Relationships From Conversational Histories Fernanda B. Viegas Scott Golder Judith Donath Speaker: Yi-Ching Huang 2007/09/04 About this paper Fernanda B. Vigas , Scott Golder , Judith Donath,

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Visualizing Email Content: Portraying Relationships From Conversational Histories

Fernanda B. Viegas Scott Golder Judith Donath

Speaker: Yi-Ching Huang 2007/09/04

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About this paper

  • Fernanda B. Viégas , Scott Golder , Judith Donath, Visualizing email

content: portraying relationships from conversational histories, Proceedings of the SIGCHI conference on Human Factors in computing systems, April 22-27, 2006, Montréal, Québec, Canada

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Email Visualization

  • Thread-based visualizations
  • Social-network visualizations
  • Temporal visualizations
  • Contact-based visualizations
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  • They are useful for showing the

networks of acquaintanceship and the temporal rhythms of interactions, but...

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  • They do not provide any clues about the

topics people discuss or the type of language they use with different members of their social circles.

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Themail

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Themail

  • Themail visualize an individual’s email

content over time

  • show keywords along a timeline
  • keywords have different colors and

sizes

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Two main questions

  • What sorts of things do I talk about with

each of my email contacts?

  • How do my email conversations with
  • ne person differ from those with other

people?

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  • Multiple layers of information
  • Yearly words: reveal the most used

terms over an entire year of email exchange

  • Monthly words: are the most

distinctive and frequency used words in email conversation over a month

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How does it work?

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Themail

  • Themail processor
  • merge multiple account
  • calculate topic words
  • TFIDF algorithm
  • Themail visualization
  • interacting with Themail
  • adjusting the time scale
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Our Idea: Bookmark Rhythms

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Main Idea

  • Show an individual’s interest change
  • ver time
  • Visualize the rhythm of interest change
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Our Approach

  • Data source from
  • social bookmarking website: del.icio.us
  • Extract multiple layer information
  • overall topic
  • topic exchange over time
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Information Processing

  • Clustering
  • Classification
  • Semantic v.s. Color analysis
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Visualization

  • overall visualization
  • tag-cloud (color & size)
  • temporal visualization
  • rhythm (timeline)
  • interact with data
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Milestone

  • 9/4 ~ 9/11
  • visualize the raw data
  • implement ConceptNet