Intermediate techniques in text analysis with R

• 9:00 am - 9:30 am: Overview of common text analysis techniques: text classification and clustering algorithms.

• 9:30 am - 10:00 am: Topic modeling: using algorithms to identify the main topics in a text corpus with - applications in communication science.

• 10:00 am - 10:30 am: Introduction to R for topic modeling, with hands-on exercises.

• 10:30 am - 11:00 am: Break.

• 11:00 am - 12:00 pm: Identify the number of topics, assess quality, and validate, with hands-on exercises.

• 12:00 pm - 1:00 pm: Lunch.

• 1:00 pm - 2:30 pm: Advanced topic modeling methods: Structural Topic Models and Seeded Topic Models, with hands-on exercises.

• 2:30 pm - 3:00 pm: Coffee Break.

• 3:00 pm - 4:30 pm: Laboratory with real-world data.

• 4:30 pm - 5:00 pm: Summary of the day’s topics and key takeaways.