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My Twitter Neighborhood
Alexander Nwala, Hassan Al-Maksousy
Tuesday, February 24, 2015
Motivation
• Online social networks are expanding rapidly
• An enormous amount of research effort targets the
analysis of social networks.
• Visualizing social networks is an important aspect of
social networks research.
• We propose a visualization project which attempts to fill
some missing functionalities in pre-existing tools as
well as augment or improve others.
• This would be done from an individuals (Twitter
user’s perspective)
Preview of data
• Twitter is our data source -
• Friend list
• Followers list
Initial Analysis
• Given that the social network is a graph,
• How should this graph be traversed (breadth-first,
depth-first)
• What are the consequence of each traversal
scheme?
• Are the standard traversal schemes sufficient?
• What are the graph theoretic properties of
individual community subgraphs
Initial Design
Our Vis Service.
Server
clients (browsers)
Development Tools
• Python for algorithm prototyping/testing
• D3 for Visualization
• Php for server-side Twitter API communication
• App. only authentication for design
• 3-legged authentication for final release
My Twitter Neighborhood::Milestones
Alexander Nwala, Hassan Al-Maksousy
Tuesday, March 31, 2015
Milestones
• Client - implemented force directed node link vis idiom
• Client - implemented adjacency matrix vis idiom
• Server - implemented 3-legged authentication
• Server - implemented breadth-first node traversal
algorithm
• Server - identified upperbound count of request to be
sent to Twitter as a variant of counting the number of
nodes in a perfect k-ary tree
• Given the request to retrieve k friends at a degree
h, the number of requests to be sent to Twitter is:
Milestones
• Server - identified upperbound count of request to be
sent to Twitter as a variant of counting the number of
nodes in a perfect k-ary tree
• Given the request to retrieve k friends at a degree
h, the number of requests to be sent to Twitter is:

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Information Visualization Project

  • 1. My Twitter Neighborhood Alexander Nwala, Hassan Al-Maksousy Tuesday, February 24, 2015
  • 2. Motivation • Online social networks are expanding rapidly • An enormous amount of research effort targets the analysis of social networks. • Visualizing social networks is an important aspect of social networks research. • We propose a visualization project which attempts to fill some missing functionalities in pre-existing tools as well as augment or improve others. • This would be done from an individuals (Twitter user’s perspective)
  • 3. Preview of data • Twitter is our data source - • Friend list • Followers list
  • 4. Initial Analysis • Given that the social network is a graph, • How should this graph be traversed (breadth-first, depth-first) • What are the consequence of each traversal scheme? • Are the standard traversal schemes sufficient? • What are the graph theoretic properties of individual community subgraphs
  • 5. Initial Design Our Vis Service. Server clients (browsers)
  • 6. Development Tools • Python for algorithm prototyping/testing • D3 for Visualization • Php for server-side Twitter API communication • App. only authentication for design • 3-legged authentication for final release
  • 7. My Twitter Neighborhood::Milestones Alexander Nwala, Hassan Al-Maksousy Tuesday, March 31, 2015
  • 8. Milestones • Client - implemented force directed node link vis idiom • Client - implemented adjacency matrix vis idiom • Server - implemented 3-legged authentication • Server - implemented breadth-first node traversal algorithm • Server - identified upperbound count of request to be sent to Twitter as a variant of counting the number of nodes in a perfect k-ary tree • Given the request to retrieve k friends at a degree h, the number of requests to be sent to Twitter is:
  • 9. Milestones • Server - identified upperbound count of request to be sent to Twitter as a variant of counting the number of nodes in a perfect k-ary tree • Given the request to retrieve k friends at a degree h, the number of requests to be sent to Twitter is: