Midterm

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Midterm

  1. 1. A large scale social network visualization Rashid Bhamjee Supervised by Dr. Benoit Gaudin
  2. 2. Project Motivation <ul><li>Many applications exist to provide a visualization of how a person and their friends are connected. </li></ul><ul><li>None provide a visualization of their greater network. </li></ul><ul><li>Provide a visual representation of how a person is connected to their friends and how their friends are connected to each other. </li></ul>
  3. 3. Problems <ul><li>An extremely large amount of data to visualize. </li></ul><ul><li>A standard graph drawing is too cluttered making it difficult to visualize meaningful information. </li></ul>
  4. 4. A Solution <ul><li>Use clustering techniques to reduce the size of the graph. </li></ul><ul><li>Two types of clustering techniques: “Classic” clustering, structural clustering. </li></ul><ul><li>Use a combination of both techniques </li></ul>
  5. 5. Classic Clustering <ul><li>Group strongly connected people together. </li></ul><ul><li>Identifies social cliques within the network. </li></ul>
  6. 6. Structural Clustering <ul><li>Merge nodes with the same connections to form a single node. </li></ul><ul><li>In the case of social networks nodes will rarely be similar; a metric must be used. </li></ul>
  7. 7. Implemented <ul><li>Downloaded HTML and parsed profile data and friend relations into a database. </li></ul><ul><li>~7,500 nodes </li></ul><ul><li>~750,000 edges </li></ul>
  8. 8. What’s Left To Do... <ul><li>Study: </li></ul><ul><ul><li>Impact of each clustering techniques. </li></ul></ul><ul><ul><li>Combine different types of clustering. </li></ul></ul><ul><li>Implementation: </li></ul><ul><ul><li>Several clustering algorithms. </li></ul></ul><ul><ul><li>Visual interface. </li></ul></ul><ul><li>Experiment on the usability of the application. </li></ul>

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