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Digital Methods - University of Lucerne

TikTok: Theories, tools and techniques for content analysis

Course Overview

This course is designed to immerse participants in the world of TikTok content analysis, grounding them in both the theoretical frameworks and practical tools needed to dissect and understand the platform’s influence. Through a blend of lectures, case studies, and interactive sessions, participants will gain insights into how TikTok shapes societal phenomena and how its content can be systematically analyzed to reveal underlying patterns and narratives.

Day 1: Theoretical Foundations

  1. Introduction and course overview
  2. Why does TikTok content matter?
  3. Collecting and sampling TikTok data
  4. Good practices and ethical considerations
  5. Development of research questions

Day 2: Practical Coding and Analysis Techniques (data: https://www.dropbox.com/scl/fo/66ww6wx3uyfmrxtofwj15/AIaEMzMwCuH73nsE-2yyuR4?rlkey=bndw19j6v0c4oy2qw27g7xpgy&st=brwh0s8k&dl=0 )

  1. Introduction to Convolutional Neural Networks (CNNs)
  2. Supervised and unsupervised image classification
  3. Advanced techniques: Automated face analysis in TikTok videos
  4. Tools for hypothesis testing
  5. Beyond the visual: Dissecting TikTok videos (audio, text, and image combined)

Day 3: Research projects

  1. Project Presentations
    • Students present their individual projects to the group
    • Peer and instructor feedback on the methodologies, findings, and interpretations
    • Group discussion on key learnings and takeaways from the workshop

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