Social network analysis using R

Social network analysis using R, available at $34.99, has an average rating of 3.35, with 21 lectures, based on 38 reviews, and has 153 subscribers.

You will learn about Explore the concept of social network analysis Learn how social network analysis can used at practical setting Creating network graphs Learn how social network graphs can be prepared in R Visualising a network This course is ideal for individuals who are Data analysts or Business analysts or R enthusiasts It is particularly useful for Data analysts or Business analysts or R enthusiasts.

Enroll now: Social network analysis using R

Summary

Title: Social network analysis using R

Price: $34.99

Average Rating: 3.35

Number of Lectures: 21

Number of Published Lectures: 21

Number of Curriculum Items: 21

Number of Published Curriculum Objects: 21

Original Price: $24.99

Quality Status: approved

Status: Live

What You Will Learn

Explore the concept of social network analysis
Learn how social network analysis can used at practical setting
Creating network graphs
Learn how social network graphs can be prepared in R
Visualising a network

Who Should Attend

Data analysts
Business analysts
R enthusiasts

Target Audiences

Data analysts
Business analysts
R enthusiasts

When it comes to data-oriented programming language, R is considered one of the top 3 in the list. Through R we can perform a staggering number of statistical data modelling functions. In this exciting course we will learn how R can be used to perform social network analysis which is one of the widely used data analysis methods these days to measure connectedness among individuals, groups and organisations. Social network analysis is used to establish and measure connectivity within transport, advertising, national security, medicine, geography, politics, social psychology, and many other fields. If you’re involved in analytics in any capacity, this course will be a huge help, teaching you how R can be used to format data for analysis, create graphs, analyse network graphs, and visualise networks. Although the course is designed in an extremely simple but informative manner, but it is still expected that you should be some basic experience of R environment to do this course. The course also comes with some sample data-sets, coding lists and R files with codes which will help you to become an expert of social network analysis. So, let’s learn how to examine the relationships and trends among networks in new and exciting ways, and discover information about how individuals in an organization interact.

Course Curriculum

Chapter 1: What is social network analysis?

Lecture 1: Introduction from the instructor

Lecture 2: Welcome message

Lecture 3: Introduction

Lecture 4: Basic concepts of social network analysis

Chapter 2: Basic introduction to R

Lecture 1: Why use R

Lecture 2: Installing packages in R

Chapter 3: Entering data into R

Lecture 1: Format data for social network analysis

Lecture 2: Customising the graph

Chapter 4: Creating basic graphs

Lecture 1: Creating basic graphs using igraph

Lecture 2: Creating different types of Social Network graphs in R

Lecture 3: Entering data from csv file

Chapter 5: Analysing network graphs

Lecture 1: Calculate network density

Lecture 2: Measure betweenness

Lecture 3: Measure edge density

Lecture 4: Analyse graphs through cliques

Lecture 5: Taking random walks in graph

Chapter 6: NetworkD3 package

Lecture 1: Introduction to NetworkD3

Lecture 2: Simple network diagram

Lecture 3: Hierarchical clustering – dendogram

Lecture 4: Sankey Network

Lecture 5: Force Network

Instructors

Dr. Sayem Hossain
Data, Research, Strategy and Evaluation Expert
HotCubator Academy
A think tank in Data, Research and Entrepreneurial thinking

Rating Distribution

1 stars: 1 votes
2 stars: 7 votes
3 stars: 6 votes
4 stars: 10 votes
5 stars: 14 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

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