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Computing In Context

Computing In Context. Web Science/Network Science. The Team. Dr. Albert Esterline (NC A&T) Taught Undergraduate/Graduate Web Science courses. Course taught since 2009. Dr. Sekharipuram S. Ravi (University of Albany) Dr. Darina Deicheva (Winston-Salem State Univ.)

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Computing In Context

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  1. Computing In Context Web Science/Network Science

  2. The Team • Dr. Albert Esterline (NC A&T) • Taught Undergraduate/Graduate Web Science courses. Course taught since 2009. • Dr. Sekharipuram S. Ravi (University of Albany) • Dr. DarinaDeicheva (Winston-Salem State Univ.) • Dr. Christo Dichev (Winston-Salem State Univ.)

  3. What is Web Science? • Integrates computer and information sciences, communication, linguistics, sociology, psychology, economics, law, political science, philosophy, digital humanities • Embraces the study of the Web as a vast universal information network of people and communities.

  4. Why study the Web? • The Web has become an unique creation of humanity. In that, with the use of technology people are more in touch with each other than ever before. • Understanding this network is what I believe Web Science is all about.

  5. How do we study the Web? • Graph Theory, but this only gets you so far. The problem is that these graphs have implied meanings of which graph theory, not by default can handle. For example, random graphs are statistically interesting and can bring out fundamental concepts of graphs, however, the Web is clearly not a random phenomenon. • Going deeper into the meaning of the graph, semantics, relationships, social aspects, economic aspects, political influences, etc….

  6. Web Science in the undergraduate CS major • Web, increasingly the platform for computation. • Cloud computing • Social networking • Software as a service

  7. Web Science in existing courses • Web Science type problems can be introduced throughout the undergrad CS curriculum. Example, suppose we examine a group of students in a club and ask about the friendship relations between members. A freshmen programmer should be able to represent a graph in a matrix and there by should be able to answer such questions as: • Of your classmates who is the most popular? • Who has the minimum number of friends?

  8. Modules for development Possible area of module development • Social networks • Economic networks • Political networks • Linguistic networks • Biological networks

  9. Tools for network analysis • NetworkX: Python-language package that is perhaps the most widely used network-science software. • CINET (CyberInfrastructure for Network Science) is a web portal developed and supported by the Network Dynamics and Simulation Science Laboratory (NDSSL) at VT that provides a computational and analytic environment for network science researchers. • Gambit: For game theory examples

  10. Undergraduate Web Science Course • Interdisciplinary • Encourage Computational Thinking • Social Network Analysis • Game theory • Agent-based modeling

  11. Goals • Develop a set of exemplars that can be adopted for use in either an undergraduate Web Science course or used to explain or introduce Web Science and computational thinking into other courses. • Develop a syllabus outlying the topics for an undergraduate course in Web Science. • Develop a few teaching modules that may also be adopted for use. • Teach either a course in undergraduate Web Science or incorporate modules and exemplars into an existing course.

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