Your SlideShare is downloading. ×
  • Like
  • Save
Data Visualisation, Axel Bruns
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×

Now you can save presentations on your phone or tablet

Available for both IPhone and Android

Text the download link to your phone

Standard text messaging rates apply

Data Visualisation, Axel Bruns

  • 787 views
Published

 

Published in Technology , Education
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
    Be the first to like this
No Downloads

Views

Total Views
787
On SlideShare
0
From Embeds
0
Number of Embeds
0

Actions

Shares
Downloads
0
Comments
0
Likes
0

Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide

Transcript

  • 1. Data Visualisation Dr Axel Bruns [email_address] http://snurb.info/
  • 2. Background
    • Social Media:
      • source of vast amounts of data and metadata
      • increasingly made immediately publicly available
      • accessible directly or through APIs
    • Enables:
      • tracking public communication and cultural participation
      • automatic analysis at (very) large scale
      • effective visualisation to identify key patterns
      • (close to) real time analysis
  • 3. Twitter : individual user stats (from http://dcortesi.com/2007/12/27/twitter-stats/ , via Jean)
  • 4. Twitter : friends networks (from http://bvlg.blogspot.com/2007/04/twitter-vrienden.html , via Jean)
  • 5. The World According to the Blogosphere The World According to The Australian (and The Sun ) (from http://www.observatoiredesmedias.com/2008/03/24/le-monde-dans-les-yeux-dun-redac-chef-lamericaine-version/ )
  • 6.  
  • 7. Last.fm : geographic distribution of users (from http://visualizinglastfm.de/einfuehrung.html )
  • 8. Where to from Here?
    • Currently:
      • more data than research ideas…
      • useful to investigate virtually any form of mediated cultural activity
      • needs to be combined with other methods – avoid data-driven research
    • Potential uses:
      • examine diffusion and evolution of ideas
        • e.g. change in listening patterns on last.fm after new album releases
        • e.g. spread of news across the Twitter network
      • investigate interconnections between different media spaces
        • e.g. interrelation between mainstream and social media
        • e.g. patterns of media embedding between social media sites
    • Needs:
      • build better tools for such research
      • develop expertise / collaborate with experts in data mining and visualisation
      • establish ethical guidelines for using and storing these data