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University of Michigan

Social Network Analysis

University of Michigan via Coursera


Week 1. Introduction
Week 2. Random Graph Models
Week 3. Centrality
Week 4. Community structure
Week 5. Small world networks
Week 6. Processes on networks
Week 7. Cool and unusual applications
Week 8. Network resilience

Taught by

Lada Adamic


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4.2 rating, based on 12 reviews

Start your review of Social Network Analysis

  • Anonymous

    Anonymous completed this course.

    My review is for the UC Davis version of the Social Network Analysis Course. This and the computer simulation course are my personal favorites in this series. The instructors are engaging and give great real-life examples to show off social networks. I learned great information about the power of a person's network, and how we actually are so connected in society (six degrees of separation!). Definitely recommended if anyone is interested in how humanity is socially connected, or just interested in learning how to analyze a social network.
  • Scott Orr

    Scott Orr completed this course.

    Social Network Analysis provided a good survey of the methods and applications in the field, covering random networks, measures of centrality, small world networks (and other topics related to the question of optimization), and the dynamic aspects of networks, such as contagion and opinion formation. Adamic's explanations were usually clear, and even a student with little knowledge of probability could have gotten the gist of most of the course material (and made use of Gephi to perform basic analysis), but equations were presented for those who wanted them, and the readings gave further detail.
  • Anonymous

    Anonymous completed this course.

    Highly recommended course if you want to get your hands dirty with real data and actual social network analysis on them. You will learn to use Ghephi software. The instructor posts in the forums herself, answering questions and fixing mistakes in quiz grading etc. Some parts may be maths heavy (sometimes marked optional and are not required for understanding the bigger picture or for quiz/exams). [I took the first iteration of the course in Sept 2012.]
  • Anonymous

    Anonymous completed this course.

    What you learn in this class is actually relevant to analyzing almost any network that can can be modeled as a graph. You will learn the subject, underlying math, some interesting and useful applications, and will use a software tools such as NetLogo, Ghephi, and R. Although programming assignments are optional, I would recommend doing them as it deepens understanding of the formulas and broadens your horizons.

  • Troddel

    Troddel completed this course.

    A good course on an interesting topic. Unfortunately easy to pass the quizes without understanding much.
  • Pete Olds completed this course, spending 5 hours a week on it and found the course difficulty to be medium.

    This was an absolutely brilliant course for me.
    In some parts challenging (many of the people on the course were really clever) - but it opened my eyes up to a whole new dimension of connectedness, methods, thinking and technology.

    The presenter was knowledgeable, but more importantly knew how to transfer that knowledge to a students - including those with a huge level of knowledge (some people on it were from LinkedIn and FB) and those like me that were completely new to the domain.

    So sorry to see that it is no longer available. If it becomes available again, take it - and persevere!
  • Anonymous

    Anonymous completed this course.

    Except for a few basic concepts, the course does not give any information one can use, and certainly does not teach the participant how to analyze networks.
  • pssGuy

    pssGuy completed this course.

    Jolly Hockey Sticks

    Took this some time ago

    Lots of different techniques employed which took some learning
  • Rey Raul Coaguila completed this course.

  • Christopher X Gerber completed this course.

  • Michael A. Alcorn completed this course.

  • Mark Henry Butler completed this course.

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