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Online Course

Social Network Analysis

University of Michigan via Coursera

(11)
428
  • Provider Coursera
  • Cost Free Online Course (Audit)
  • Session In progress
  • Language English
  • Certificate Paid Certificate Available
  • Effort 5-7 hours a week
  • Duration 5 weeks long
  • Learn more about MOOCs

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Overview

This course is designed to quite literally ‘make a science’ out of something at the heart of society: social networks. Humans are natural network scientists, as we compute new network configurations all the time, almost unaware, when thinking about friends and family (which are particular forms of social networks), about colleagues and organizational relations (other, overlapping network structures), and about how to navigate delicate or opportunistic network configurations to save guard or advance in our social standing (with society being one big social network itself). While such network structures always existed, computational social science has helped to reveal and to study them more systematically. In the first part of the course we focus on network structure. This looks as static snapshots of networks, which can be intricate and reveal important aspects of social systems. In our hands-on lab, you will also visualize and analyze a network with a software yourself, which will help to appreciate the complexity social networks can take on. During the second part of the course, we will look at how networks evolve in time. We ask how we can predict what kind of network will form and if and how we could influence network dynamics.

Syllabus

Getting Started and Formalizing Networks
-In this module, you will be introduced to the concept of networks. You will be able to define networks and identify how data is transformed and analyzed in a network. You will able be able to discuss how to formalize networks.

Social Network Analysis
-In this module, you will be able to discuss the structure of networks and be able to explain how a person can be the center of one. You will be able to discover the different types of language that networks use and be able to identify the three types of network measurements.

Analyzing a Network with Software
-In this module, you will begin with a social network analysis lab activity. You will be able to do data wrangling of databases and visualize a network. You will be able to analyze a social network and also be able to examine other social network analysis through case studies.

Network Evolution
-In this module, you will be able to identify the different types of social networks. You will be able to discuss what mechanisms generates these different types of networks and you will be able to explain how networks move from being static to dynamic.

Growing Networks and Making Predictions
-In this module, you will be able to examine theoretical predictions of networks. You will be able to calculate basic math problems and be able to discuss how to make networks more efficient and stable.

Taught by

Lada Adamic

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Reviews for Coursera's Social Network Analysis Based on 11 reviews

  • 5 stars 36%
  • 4 stars 55%
  • 3 star 0%
  • 2 star 0%
  • 1 star 9%

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  • 1
Scott O
by Scott 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.
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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.]
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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.

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Anonymous
Troddel completed this course.
A good course on an interesting topic. Unfortunately easy to pass the quizes without understanding much.
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Pete O
by Pete 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!
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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.
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Anonymous
pssGuy completed this course.
Jolly Hockey Sticks

Took this some time ago

Lots of different techniques employed which took some learning
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Rey C
by Rey completed this course.
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Michael A
by Michael completed this course.
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Mark B
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