PLEASE NOTE: This is a supplement to the Mining Social Media course in the Data Society Network Analysis series. The course will walk you through how to pull large quantities of data from Twitter and clean it for analysis.
Identify key influencers and discovers important connectors
Create a message propagation strategy and simulate it in a model
Analyze networks and visualize them in dynamic graphs
|Prerequisites||Intro to Network Analysis,
Mining Social Media
|Practice||2 to 5 hours|
Syllabus: Mining the Twitter API (SUPPLEMENT)
This course is designed for students who have taken Data Society’s Introduction to Network Analysis course and Mining Social Media course. This short supplement teaches students how to pull large quantities of data from Twitter’s free API service, clean it, and merge it.
By the end of this supplement, students will be able to:
1. Identify key influencers and discovers important connectors
2. Create a message propagation strategy and simulate it in a model
3. Analyze networks and visualize them in dynamic graphs
1. Setting up the data (11 min)
2. Automating data collection (11 min)
3. Cleaning Twitter data (10 min)
Total instructional time: 32 min
- 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
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.