In the second session, participants will engage in hands-on coding to apply facial emotion recognition techniques using the Python packages FER and DeepFace. Working in Google Colab, we’ll analyze a sample set of images as a case study, demonstrating how to generate and interpret emotion data from the facial expressions of audiences. The session will also guide participants in comparing outputs across tools and validating results. By the end of the workshop, attendees will be equipped with practical skills to begin integrating facial emotion analysis into their research projects. Participants are required to bring laptops with access to Google Colab for the coding portion.

Sang Jung Kim, assistant professor in the School of Journalism and Mass Communication, will run the workshop.

Register for the workshop here!

Note: In order to attend Part 2 of this workshop, participants must attend Part 1, Foundations of Computer Vision for Social Scientists