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Social Network Analysis Coursera

Highlights
Tuition fee
Unknown
Tuition fee
Unknown
Duration
7 days
Duration
7 days
Apply date
Anytime
Unknown
Apply date
Anytime
Unknown
Start date
Anytime
Unknown
Start date
Anytime
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Taught in
English
Taught in
English

About

This Social Network Analysis course offered by Coursera in partnership with UC Davis is designed to quite literally ‘make a science’ out of something at the heart of society: social networks. 

Overview

 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 Social Network Analysis course offered by Coursera in partnership with UC Davis, 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.

What you'll learn

  • Define networks and discover the languages networks use.

  • Analyze a social network through data wrangling and visualizing a network.

  • Discuss what mechanisms generate networks.

  • Examine social networks analysis using case studies.

Programme Structure

Course structure:

  • Data Wrangling
  • Network Measures 
  • Network Measures 
  • Influentials
  • Who's Influential?
  • Twitter Cascades

Key information

Duration

  • Part-time
    • 7 days
    • 10 hrs/week

Start dates & application deadlines

You can apply for and start this programme anytime.

Language

English

Delivered

Online
  • Self-paced

Campus Location

  • Mountain View, United States

What students do after studying

Join for free or log in to access our complete career info list.

Academic requirements

We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

English requirements

We are not aware of any English requirements for this programme.

Other requirements

General requirements

  • Beginner level
  • No previous experience necessary
  • This course is aimed at learners interested in data science and social research who want to develop skills in analyzing, visualizing, and understanding social networks and their dynamics using computational methods.

Tuition Fees

Additional Details

Course is free for the first 7 days. After 7 days, the course can be accessed with the Coursera Plus Subscription

Funding

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