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Social Network Analysis

University of Michigan via Coursera

11 Reviews 421 students interested
Found in Data Science

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Overview

Everything is connected: people, information, events and places, all the more so with the advent of online social media. A practical way of making sense of the tangle of connections is to analyze them as networks. In this course you will learn about the structure and evolution of networks, drawing on knowledge from disciplines as diverse as sociology, mathematics, computer science, economics, and physics. Online interactive demonstrations and hands-on analysis of real-world data sets will focus on a range of tasks: from identifying important nodes in the network, to detecting communities, to tracing information diffusion and opinion formation.

Syllabus

Week 1: What are networks and what use is it to study them?
Concepts: nodes, edges, adjacency matrix, one and two-mode networks, node degree
Activity: Upload a social network (e.g. your Facebook social network into Gephi and visualize it ).
Week 2: Random network models: Erdos-Renyi and Barabasi-Albert
Concepts: connected components, giant component, average shortest path, diameter, breadth-first search, preferential attachment
Activities: Create random networks, calculate component distribution, average shortest path, evaluate impact of structure on ability of information to diffuse
Week 3: Network centrality
Concepts: betweenness, closeness, eigenvector centrality (+ PageRank), network centralization
Activities: calculate and interpret node centrality for real-world networks (your Facebook graph, the Enron corporate email network, Twitter networks, etc.)
Week 4: Community
Concepts: clustering, community structure, modularity, overlapping communities
Activities: detect and interpret disjoint and overlapping communities in a variety of networks (scientific collaborations, political blogs, cooking ingredients, etc.)
Week 5: Small world network models, optimization, strategic network formation and search
Concepts: small worlds, geographic networks, decentralized search
Activity: Evaluate whether several real-world networks exhibit small world properties, simulate decentralized search on different topologies, evaluate effect of small-world topology on information diffusion.
Week 6: Contagion, opinion formation, coordination and cooperation
Concepts: simple contagion, threshold models, opinion formation
Activity: Evaluate via simulation the impact of network structure on the above processes
Week 7: Cool and unusual applications of SNA
Hidalgo et al. : Predicting economic development using product space networks (which countries produce which products)
Ahn et al., and Teng et al.: Learning about cooking from ingredient and flavor networks
Lusseau et al.: Social networks of dolphins
Activity: hands-on exploration of these networks using concepts learned earlier in the course
Week 8: SNA and online social networks
Concepts: how services such as Facebook, LinkedIn, Twitter, CouchSurfing, etc. are using SNA to understand their users and improve their functionality
Activity: read recent research by and based on these services and learn how SNA concepts were applied

Taught by

Lada Adamic

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Reviews for Coursera's Social Network Analysis
4.1 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
4.0 5 years ago
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
4.0 7 years ago
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
5.0 7 years ago
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
4.0 5 years ago
Troddel completed this course.
A good course on an interesting topic. Unfortunately easy to pass the quizes without understanding much.
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this review helpful
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Pete O
5.0 2 years ago
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
1.0 6 years ago
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
4.0 6 years ago
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
4.0 4 years ago
by Rey completed this course.
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Michael A
5.0 4 years ago
by Michael completed this course.
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Christopher G
4.0 4 years ago
by Christopher completed this course.
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Mark B
5.0 4 years ago
by Mark completed this course.
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