Starting with Social Network Analysis
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- Conceptualize your own social network study
- Collect social network data yourself
- Have an idea of how to analyze your social network data
- Understand social network research more deeply
- You should be interested in social network analysis (as a method used in research or business).
- Attention: This course is not about social media -- but if you want to apply social network analysis to social media, please join!
In this course, you will learn everything you need to get started with doing social network analysis (SNA). Taking this course will be the fastest way for you to learn about the nature of this unique perspective and to understand its major concepts. Additionally, I will provide executive summaries of foundational social network studies (which will be continously updated) to get you started with your literature work.
Specifically, you will learn...
- …about the basic concepts that we have to understand to do and read about social network analysis.
- …about everything you need to set up your own network study (or to understand the setup of another social network study).
- …about common strategies to collect relational data.
- …how to analyse network data.
- …what software packages exist that may help you with social network data collection or data analysis.
- …about influential texts in the field of social network research.
There are plenty of exercises included in this course to help you solidify your learning.
Who will be your instructor?
My name is Dominik E. Froehlich and I am an active researcher of social networks for quite a few years now. I mostly study networks in the domain of learning and instruction, but occasionally I ventured to other fields, such as organization and management. I'm well published in this field in terms of academic articles, I'm editing a book about social network analysis with a well-known publisher, and my work on social networks has won international academic awards. Speaking of awards: I also won awards for my (online) teaching -- so hopefully this translates into a great learning experience for you. I'm always available for questions and suggestions for further lections in the course in order to make the course even more relevant to you!
Is this course right for you?
While this course is explicitly targeted at researchers at any level (including students, of course!), organizational consultants and managers may find the course useful to understand the basics of how work is often organized in an informal way.
Need even more information?
Need more information? Check out the preview videos, the curriculum, or this list of learnings... and don't forget that you can get a refund within 30 days, no questions asked.
You will learn...
- …why social network analysis is receiving so much interest these days---and why it will pay off for you to learn about it.
- …about the general perspective that social network analysis takes and how this perspective is different or novel.
- …about how we can define the nature of social networks.
- …about a central concept of social network analysis: nodes, which are also called vertices or actors.
- …about modes and the disctinction between one-mode networks and two-mode networks.
- …about another important concept of social network analysis: egdes, which are also called ties or arcs or relationships.
- …about how you may classify differnt types of networks.
- …how networks are made up by vertices and edges.
- …about the difference between sociocentric and egocentric networks in social network analysis.
- …about what types of research questions are possible to answer using social network analysis.
- …about the different units of analysis that you may investigate using social network analysis.
- …about the boundary specification problem; a very important challenge in any social network study.
- …about theorizing within social network studies.
- …about the key features of social capital theory.
- …about the key features of cognitive social structures.
- …about the key features of balance theory.
- …about the key features of homophily.
- …about the quality of relational data that we need for social network analysis.
- …about the specificities of collecting quantitative network data via a survey.
- …that ethical considerations are especially important when conducting social network analysis.
- …about two major ways of storing quantitative network data: the matrix format and the edgelist format.
- …how to present quantitative data in different formats (edgelist, matrix, and the visual representation) and how to prepare your data accordingly.
- …about nodal degree, a very basic put important centrality metric frequently used in social network analysis.
- …about betweenness, an often used metric for centrality or brokerage in networks.
- …about closeness, an indicator for distance between one node and the rest of the network.
- …where to download the open source software Gephi, which we will use for network visualization.
- …how to navigate in Gephi.
- …to calculate key metrics of social network analysis in Gephi.
- …about how to apply layouting algorithms in Gephi.
- …how to change the appearance of your network graph based on previously calculated metrics.
- …where to download the software Vennmaker, which we will use for network data collection.
- …how to navigate in VennMaker and how this software may help you in collection relational data.
- ...and more...
- Researchers at any level seeking to apply social network analysis quickly
- Students wanting to learn about social network analysis
- Reviewers and staff of funding agencies who want to get a quick overview of the field
- Managers and consultants who want to understand the informal organization of work
In this lecture you will learn about the learning goals of this course on social network analysis (SNA).
In this lecture you will learn why social network analysis is receiving so much interest these days---and why it will pay off for you to learn about it.
In this lecture you will learn about betweenness, an often used metric for centrality or brokerage in networks.
In this lecture you will learn how to change the appearance of your network graph based on previously calculated metrics.