Advanced techniques in text analysis with R

• 9:00 am - 9:30 am: Overview of text classification techniques beyond topic modeling: unsupervised and supervised methods.

• 9:30 am - 10:30 am: Unsupervised text classification: Text scaling, correspondence analysis, clustering, and applications in communication science, with hands-on exercises.

• 10:30 am - 11:00 am: Break.

• 11:00 am - 12:00 pm: Laboratory with real-world data sets.

• 12:00 pm - 1:00 pm: Lunch.

• 1:00 pm - 2:00 pm: Supervised classification: using R to classify text data into different categories, with an overview of algorithms and hands-on exercises.

• 2:00 pm - 3:00 pm: Laboratory with real-world data sets.

• 3:00 pm - 3:30 pm: Coffee Break.

• 3:30 pm - 4:30 pm: Overview of other text analysis techniques, with hands-on exercises.

• 4:30 pm - 5:00 pm: Conclusion and wrap-up of the seminar.