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Social Network Analysis: The Networks Connecting People

Explore the structure and dynamics of different types of social networks and use models to identify patterns of social influence.

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Social Network Analysis: The Networks Connecting People
  • Duration

    3 weeks
  • Weekly study

    3 hours
  • 100% online

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Learn how norms, viruses and info spread through social networks

Have you ever wondered how a tiny virus can spread across the planet, how people share false information through social media, or why people abide by group norms, even when they are harmful? With easy-to-use computational models you will explore the social dynamics explaining these processes.

This brand-new course from computational social science experts at University College Groningen and the University of Warsaw explores how networks form, and how they impact the spreading of different types of information in society.

Discover social network analysis tools, structures, and modelling

On this course, you’ll get to grips with the basics of social network theory, before considering how different social exchanges impact network structures and dynamics of opinion and product choice.

You’ll learn how the way we communicate, and even share viruses, is shaped by social network structures that existed in our tribal history, and have expanded in modern society.

Identify patterns of social interaction and explore social influence theory

You’ll learn how social influences play out in larger networks, as you explore what impact small scale tribal mechanisms, like local norms, have on global network dynamics.

Study social network theory with computational social science (CSS) experts

This course has been designed as a collaboration between University College Groningen, the University of Warsaw, and Humboldt Institute for Internet and Society.

Warsaw and Groningen are experts in CSS, and this course offers students the chance to learn from four leading social science scholars.

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Skip to 0 minutes and 4 seconds Have you ever wondered why it is so difficult to control the outbreak of a virus? Are you sometimes surprised that conspiracies, such as the flat earth, persist? Networks are the key for understanding both these seemingly unrelated issues. Viruses, ideas, opinions– they all spread through the many connections that we share. To better understand the network dynamics underlying the spreading of new ideas, practices, viruses, and fashions, this module will introduce you to the core principles of network theory. You will discover that despite having the internet, often, network effects happen just like 10,000 years ago when we were tribal hunter-gatherers. Networks are difficult to study. They involve many people.

Skip to 1 minute and 3 seconds And their influences are often difficult to observe and stretch out over longer periods of time, sometimes years or even generations. Therefore, social scientists increasingly use computer simulations to study the dynamics of social networks. This module introduces you to network theory. And using easy-to-use computer simulations, no programming needed, you can explore, for yourself, how networks grow and how information spreads via these networks. After completing this module, you will have a basic understanding of how networks affect opinion dynamics and how viruses, rumours, and information on products and services spread, to name a view of the many applications. If you want to know more about how networks influence our lives, join us.

Syllabus

  • Week 1

    Living in communities

    • Welcome to Social Networks!

      Get to know your lead educator, introduce yourself, and learn a bit about what to expect in the course.

    • Welcome to the tribe!

      An introduction to the small tribal network that we all come from.

    • Key Concepts: Nodes and Links

      In this activity you will be introduced to two key concepts of social networks: the links connecting the nodes.

    • An Early Social Computational Model

      The Game of Life is one of the important starting points of computational social science, which inspired many people. You will learn how complex patterns can grow out of simple rules of interaction.

    • Small worlds

      In this activity you will explore how clustering and path lengths differ for networks that are regular, random, or display small world properties.

    • Wrapping up Week 1

      We look back at the first week and ahead to what is to come in Week 2.

  • Week 2

    The larger agricultural society and hubs

    • How many people do we know in a network?

      In this week we will explore the role of people having many contacts, the so-called hubs or superspreaders’ have on network dynamics.

    • How popularity grows

      In this activity we discuss preferential attachment and hubs.

    • How do hubs function as superspreaders in society?

      In this activity we will reflect on the role of so-called weak links, as opposed to hubs

    • More than viruses: sharing information

      In this activity we address the spreading of information through a network. Because these influences require more conscious processing than the spreading of a virus, the network dynamics are different.

    • Obeying the norm

      In this activity we address the spreading of and norms through a network. Because these influences require more conscious processing than the spreading of a virus, the network dynamics are different.

    • Wrapping up Week 2

      We look back at the second week and ahead to what is to come in Week 3.

  • Week 3

    Global society and social influences

    • Expanding networks in our recent history

      In this activity we will reflect on how our networks developed in modern times

    • Influencers and their impact on society

      In this activity we will focus on how influencers affect the diffusion of new ideas and practices in a society

    • Wrap up - Understanding network dynamics

      In this final activity we wrap up the module, and reflect on the predictability of social network dynamics

When would you like to start?

Start straight away and learn at your own pace. If the course hasn’t started yet you’ll see the future date listed below.

  • Available now

Learning on this course

You can take this self-guided course and learn at your own pace. On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.

What will you achieve?

By the end of the course, you‘ll be able to...

  • Compare how different network structures affect social dynamics
  • Identify how key properties of social networks connect with the spreading of different influences such as viruses, norms and properties of products
  • Experiment with different social influences and network structures and how they impact diffusion dynamics
  • Assess situations where “small scale tribal mechanisms” such as local norms have an impact on global network dynamics

Who is the course for?

This course is designed for anyone interested in developing their understanding of the basic concepts of social network theory and how information, viruses, and norms spread through society.

It will be particularly useful for professionals dealing with situations where social influences and processes of diffusion play a role, such as in the context of public policy, business, marketing, and healthcare.

If you already study social science and would like to develop your skills in maths, computers, and formal modelling, this course will help.

What software or tools do you need?

For the models used in the course we highly recommend that these are done on a large screen, either a PC, laptop or a tablet at least, as the models will not be easy to operate on a phone.

Who will you learn with?

I'm a social scientist working at the University College Groningen & Faculty of Economics and Business. Also I'm managing the Groningen Center for Social Complexity Studies. Twitter: @GCSCS_RuG

Who developed the course?

University of Groningen

The University of Groningen is a research university with a global outlook, deeply rooted in Groningen, in the north of the Netherlands.

University of Warsaw

University of Warsaw is the leading research university and the largest higher education institution in Poland, with a comprehensive portfolio of research and teaching activities.

Alexander von Humboldt Institute for Internet and Society

The Alexander von Humboldt Institute for Internet and Society is exploring digitalisation together with economic, political and civil society stakeholders.

ACTiSS

Action for Computational Thinking in Social Sciences (ACTISS) is an Erasmus+ project aimed to develop engaging and accessible online courses introducing the basics of computational social sciences.

Endorsers and supporters

funded by

Erasmus+
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Sale price available until 6 December 2021 at 23:59 (UTC). T&Cs apply.

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