Python - Social Data Mining

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Social Data Mining With Python

taught by Shilad Sen

Aim of Course:

Humans have taken their voices online en-masse. Over one billion people engage their friends via Facebook. Twitter publishes half a billion tweets each day.  In this online course, “Social Data Mining with Python,” you will use Python to extract valuable signals from these huge, chaotic datasets to explain collective behavior and create computational knowledge bases. Using Python, you will analyze user-generated content such as movie ratings, online comments, status updates, and friendship networks. You will learn algorithms from the fields of social network analysis, text analysis, and recommender systems. Finally, you will gain experience with pragmatic workflows that leverage social APIs to reveal human insights in your own projects.

This course may be taken individually (one-off) or as part of a certificate program.

Course Program:

Week 1: Recommendation algorithms

  • Refresher on Python data structures
  • Streaming large datasets
  • Filtering noise in long-tailed datasets
  • Algorithmic time complexity in a nutshell
  • Introduction to recommendation algorithms
  • Case study: If you liked “Star Wars” you’ll like ??

Week 2: Introduction to text analysis in Python

  • Python’s “yield” keyword
  • Tf/Idf weighting
  • Algorithms that identify distinctive language
  • K-means clustering
  • Case study: Distinctive language in subreddit communities

Week 3: Social APIs

  • A taxonomy of social APIs and Python interfaces to them
  • Practical workflows when using social APIs
  • Case study: Datasift & sentiment analysis on Twitter

Week 4: Social network analysis

  • Network data structures in Python
  • Your Facebook graph: visualization and community detection
  • Using the Gephi network visualization tool
  • Case study: Inducing network graphs - the landscape of movies


The homework in this course consists of short answer questions to test concepts, guided exercises in writing code and guided data analysis problems using


This course also has example software codes, supplemental readings available online.

Social Data Mining With Python

Who Should Take This Course:

Programmers and statisticians familiar with Python who want to learn how to do analysis of text and social network date; analysts who know some Python and who want to deepen their Python knowledge by learning how to mine social data.



Organization of the Course:

This course takes place online at the Institute for 4 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.

Time Requirement:
About 15 hours per week, at times of  your choosing.

Students come to the Institute for a variety of reasons. As you begin the course, you will be asked to specify your category:

  1. You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
  2. You may be enrolled in PASS (Programs in Analytics and Statistical Studies) that requires demonstration of proficiency in the subject, in which case your work will be assessed for a grade.
  3. You may require a "Record of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's).  For those successfully completing the course,  CEU's and a record of course completion will be issued by The Institute, upon request.
This course is also recognized by the Institute for Operations Research and the Management Sciences (INFORMS) as helpful preparation for the Certified Analytics Professional (CAP®) exam, and can help CAP®analysts accrue Professional Development Units to maintain their certification .

Course Text:

All course materials will be provided during the course.


The required software is Python Programming Language.

Social Data Mining With Python

May 26, 2017 to June 23, 2017October 20, 2017 to November 10, 2017May 25, 2018 to June 22, 2018October 19, 2018 to November 16, 2018

Course Fee: $549