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Social Network Analysis

Learn how to analyze social structures using network and graph theory.

  • Schedule

    18-20 January 2022

    18.30 – 21.30 (WIB)

  • Online-Interactive Learning

    Via Zoom

  • Investment

    Rp. 1.500.000

GET TICKETS:

Course Summary

We are social creatures, and social interaction is one of our basic needs. Currently, we utilize multiple social media platforms to connect with our loved ones.

We can interact with the people we care about faster and are not limited by geographical areas using social media. Interactions between users on social media produce data that we can analyze to understand the relationship between users.

This 3-days online workshop is a beginner-friendly Social Network Analysis with R. We will analyze information from social media (Twitter) to build network activity using graph analysis. We will provide participants with hands-on examples and a rich interactive experience throughout the online course. One Instructor and two Teaching Assistants will help participants troubleshoot or help with any difficulties encountered.

NOTE: This workshop will be delivered in Bahasa Indonesia.

LEARNING OUTCOMES

Upon completion of this workshop, you will be able to:

  • Work with R and tidyverse for data cleansing and manipulation processes.
  • Understand graph theory and graph metrics.
  • Build communities and calculate metrics.
  • Visualize network using tidygraph.

Syllabus

  • Introduction to R for data science.
  • Working with RStudio environment.
  • Basics control statement in R.
  • Data manipulation and processing with R tidyverse.
  • Graph theory: directed and undirected graph
  • Graph metrics: centrality and modularity
  • Data gathering using Rtweet (Twitter API).
  • Feature engineering.
  • Build nodes, edges, and graph dataframe.
  • Build communities and calculate metrics.
  • Visualize network using tidygraph.

STUDENT TESTIMONIALS

This testimonial video is taken after our previous Online Data Science Series: Time Series Analysis for Business Forecasting.

LEARN FROM ANYWHERE

Our learning format is online-interactive, you will feel the interactive experience as if you were present in a physical classroom. You can access the class using your Zoom account on pre-defined dates.

  • LEARN AT YOUR OWN PACE

    Zoom recording, course Books (PDF & HTML files), the dataset for practice, reference notes, and working files are accessible through our Learning Management System account.

  • PROOF YOUR MASTERY

    Show current and prospective employers of your mastery with a signed certificate of completion.

  • CONNECT WITH LIKE MINDED PEOPLE

    Be a part of our data-passionate community with 5000+ members and 1000+ alumni.

FOR ABSOLUTE BEGINNERS

Workshops in this series are tailored to casual programmers and non-programmers that are taking their first steps into data science. It assumes no prior knowledge or academic background, and attendees will be introduced to the beautiful art of writing R / Python code to produce data visualization and build machine learning models. The workshop has a gentle learning slope that is designed with non-technical professionals and academics in mind.

Yes, you can still attend the workshop as it is a beginner-friendly workshop.

Our system will send you an email containing a link and details to join a Google Classroom.

Online learning will be conducted via Zoom.us, Link to join the Zoom Class will be announced via Google Classroom.

Learning materials can be obtain via Google Classroom

Yes, you will receive a certificate of completion.

YOUR INSTRUCTOR

DAVID TAHI ULUBALANG

Having a wide variety of industrial experiences, David Tahi Ulubalang has picked up a lot of angles in dealing with data-related cases. He majored in Computer Science from IPB and is passionate about teaching machine learning and data visualization.

David is one of 5 holders of RStudio Trainer Certification in Indonesia. He has conducted numerous consultative training for BCA, Ministry of BUMN, PT Indo Kordsa, PT Indo Tambangraya Megah, to name a few.