
Create interactive visualizations with clickable charts, graphs, maps and networks

Publish dynamic graphs and applications to your blog or website

Collect and manipulate data from almost any website, saving you time and creating new possibilities
Prerequisites | Intro to Network Analysis |
Instruction | 2 hours, 40 min |
Practice | 10 to 15 hours |
Syllabus: Mining Social Media
By the end of this course, students will be able to:
Identify key influencers and discover important connectors
Create a message propagation strategy and simulate it in a model
Analyze networks and visualize them in dynamic graphs
Assessment:
- Concept reviews: these are comprised of short five question quizzes that cover the most important concepts and ideas in each lesson. They encourage holistic understanding and are multi-faceted question types (i.e. drag and drop, fill-in-the-blanks, matching, etc).
- Exercises: these are additional videos that cover the coding functions in the instructional video in more depth. They are project-based and include coding templates for students to strengthen their skills outside of the course.
Materials provided:
- Accompanying PDFs to use as reference materials
- R code templates from the instructional videos and exercises
- Data sets used in the instructional videos and exercises
Course Outline
1. Gathering social media data (27 min)
What is social media today?
Accessing the Twitter API
Formatting social media data
Cleaning social media data
2. Building social media networks (36 min)
Visualizing social media networks
Visualizing interactive networks
Visualizing hierarchical networks
Calculating network metrics
3. Analyzing your network (35 min)
Identifying key connectors
Measuring betweenness
Identifying most important nodes
Calculating importance
4. Analyzing network effects (36 min)
Calculating Twitter networks
Cascading network effects
Simulating network effects
Automating network effects
5. Simulating network dispersion (31 min)
Generating network effects data
Simulating network dispersion
Animating network dispersion
Additional tips and resources
Total instructional time: 2 hrs, 35 min

Merav Yuravlivker
Merav Yuravlivker is a nationally ranked instructor and co-founder of Data Society. She used data-driven strategies in the classroom to maximize educational outcomes and has over 10 years of experience in instructional design, training, and teaching. Merav has helped bring new insights to businesses and move their organizations forward through implementing data analytics strategies.
Course Forum
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