Dr. Frank McCown
Science 200
TR 2:30 - 3:45 pm
Spring 2013

Class links

• Syllabus
• A Plea for Integrity
• Easel

Slides

1. Studying the Web
   • Introduction to Web Science
   • Web Architecture
   • Web Characterization
   • Web Archiving
2. Web Search Engines
   • Searching the Web
   • How Does a Web Search Engine Work? Part 1
   • Building a Web Crawler in Python
   • How Does a Web Search Engine Work? Part 2
3. Social Networks and the Web
   • Social Networks
   • Graph Partitioning
   • Homophily, Affiliation & Social Influence
   • Visualizing Social Networks
4. Collective Intelligence
   • Collective Intelligence
   • Recommender Systems
   • Clustering Algorithms
   • Document Filtering

1. Studying the Web
   • Introduction to Python
   • Web Structure
   • Web Crawler
2. Web Search Engines
   • Search Queries
   • TF-IDF
   • PageRank and HITS
3. Social Networks and the Web
   • Triadic Closure and Tie Strength
   • Friendship Paradox
   • Nicholas Christakis: Sociology
   • Embeddedness and Betweenness
   • Visualize Your Facebook Social Graph
4. Collective Intelligence
   • Movie Recommendations
   • Clustering Algorithms

• Search Engine
• Social Network
• Movie Recommendations

• Python Quick Guide
• Python Documentation

• Dr. Nelson's Web Science course at ODU
• Web Science Trust
• Presentations from Leslie Carr's Web Science course at Univ of Southampton

This material is based upon work supported by the National Science Foundation under Grant No. 1008492 (WAC). Any opinions, findings and conclusions or recomendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).

Recommended Books

An Introduction to Search Engines and Web Navigation

Networks, Crowds, and Markets: Reasoning About a Highly Connected World

Programming Collective Intelligence