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Sociology E-161 Big Data: What is it?      Download Syllabus

Instructor: Burak Eskici - eskici@fas.harvard.edu - burak.eskici@gmail.com - 617 949 9981 - WJH (650)

Office Hours:Thursdays 3pm-4.30pm or by appointment

Harvard Extension School CRN 14865

Course Description: A tremendous amount of data is now being collected through websites, mobile phone applications, credit cards, and many more everyday tools we use extensively. What is currently done and what can we do with this precious resource? This big data course looks under the hood. It explores the logic behind the complex methods used in the field (not the methods itself). We then explore how big data research is designed with real life examples of cutting-edge research and guest lecturers from Facebook, Twitter and Google. By the end of the class students will be competent in the field and be able to conduct a research design using big data.

Course Outline       

              Go to Virtual Classroom

              Download Lecture Slides

              Assignment Answer Keys

  • W1. (Sep 1)      Introduction and Sociological Roots    click here
  • W2. (Sep 8)      Social Network Analysis I   click here
  • W3. (Sep 15)    Social Network Analysis II  click here
  • W4. (Sep 22)    Social Network Data and Visualization click here
  • W5. (Sep 29)    Random Networks and Scale Free Networks click here
  • W6, (Oct 6)       Big Data: Paradigm Shift? click here
  • W7. (Oct 13)     Fitting a Model to Data click here
  • W8. (Oct 20)     Machine Learning click here
  • W9. (Oct 27)     Similarity, Neighbors, and Clusters click here
  • W10. (Nov 3)     Midterm Review click here
  • W11. (Nov 10)   Representing and Mining Text click here
  • W12. (Nov 17)   Data Visualization click here
  • W13. (Nov 24)   Big Data Applications I click here
  • W14. (Dec 1)     Big Data Applications II click here
  • W15. (Dec 8)     Ethics and Information Security click here
  • W16. (Dec 15)   Review

 

Course Requirements

  • Weekly Readings
  • Short Paper Assignments (4)  (36%)
  • Midterm Exam     (24%)                 
  • Final Paper     (40%)

Course Summary:

Course Summary
Date Details Due