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The Structure of Scientific Collaboration Networks & Research Funding Networks

The Structure of Scientific Collaboration Networks & Research Funding Networks. CS790g Complex Networks Jigar Patel November 30 th 2009. Outline. Scientific Collaboration Networks Introduction Results Conclusions Research Funding Networks Project Idea

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The Structure of Scientific Collaboration Networks & Research Funding Networks

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  1. The Structure of Scientific Collaboration Networks&Research Funding Networks CS790g Complex Networks Jigar Patel November 30th 2009

  2. Outline • Scientific Collaboration Networks • Introduction • Results • Conclusions • Research Funding Networks • Project Idea • Data Collection Techniques & Problems • Noise in Data • Data Processing Issues • Data/Network Analysis? • Summary • Questions

  3. 1.Scientific Collaboration Networks 1. Introduction • What is the idea behind it? • Representation as a graph • Interest in studying Social Network • Stanley Milgram experiment • Problems with social network studies • Labor intensive and size of the network can be mapped is limited • Highly subjective • Movie actors network example • Scientific Collaboration Networks • Data sources (MEDLINE), SPIRES, NCSTRL • Data between 1995-1999

  4. 1.Scientific Collaboration Networks 2. Results • Number of Authors

  5. 1.Scientific Collaboration Networks 2. Results • Mean Papers per Author and Authors per Paper

  6. 1.Scientific Collaboration Networks 2. Results • Number of Collaborators

  7. 1.Scientific Collaboration Networks 2. Results • The Giant Component

  8. 1.Scientific Collaboration Networks 2. Results • Clustering

  9. 2. Research Funding Network 1. Project Idea Institute 1 Grant 1 Common Research Topic Grant 1 Institute 3 Grant 3 Grant 3 Grant 2 Grant 2 Institute 2

  10. 2. Research Funding Network 2. Data Collection Techniques & Problems • Custom Application • MySQL Database for local storage • Time consuming • Limitation on number of queries can be made to server • Proxy server issue • Data parsing issues • Unknown field size

  11. 2. Research Funding Network 3. Noise in Data • Duplicate organization names • Multiple entries for the same organization • Duplicate awards • Too many PIs without an award 4. Data Processing Issues • Large dataset • 470K+ PIs, 16K+ Organizations, 290K+ awards • Takes too many queries to generate network file. • Very large dataset for the visualization

  12. 2. Research Funding Network 5. Data/Network Analysis • Complex Network Theories • Very abstract properties of the network • Average path length, degree distribution, clustering coefficient, giant component size, betweenness, closeness, prestige etc.. • Statistical Theories • Gives other perspective on data • Average money, minimum, maximum, histogram, total amount distributed, median, percentages, timeline etc.. • Data analysis by program, organization or combination of one or many factors

  13. 3. Summary • Social Network Study • It is always interesting and helps understand human nature. • Reveals the relationship between researchers in different scientific community • +Research Funding Network • Shows money distribution • Statistical side of the data • Very interesting and has never been generated

  14. Questions?

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