Unsupervised Machine Learning II

Methodenseminar: Session 10

Participate

🖥️ Slides

📋 Showcase

Practice

✍️ Exercise

Suggested readings

Topic Modeling

• Chang, J., Boyd-Graber, J., Gerrish, S., Wang, C., & Blei, D. (2009). Reading tea leaves: How humans interpret topic models. 32, 288–296.

• Chen, Y., Peng, Z., Kim, S.-H., & Choi, C. W. (2023). What We Can Do and Cannot Do with Topic Modeling: A Systematic Review. Communication Methods and Measures, 17(2), 111–130. https://doi.org/10.1080/19312458.2023.2167965

• Egger, R., & Yu, J. (2022). A topic modeling comparison between LDA, NMF, Top2Vec, and BERTopic to demystify twitter posts. Frontiers in Sociology, 7, 886498. https://doi.org/10.3389/fsoc.2022.886498

• Friemel, T. N. (2017). Social Network Analysis (J. Matthes, C. S. Davis, & R. F. Potter, Eds.; 1st ed., pp. 1–14). Wiley. https://onlinelibrary.wiley.com/doi/10.1002/9781118901731.iecrm0235

• Hase, V. (2023). Automated Content Analysis (F. Oehmer-Pedrazzi, S. H. Kessler, E. Humprecht, K. Sommer, & L. Castro, Eds.; pp. 23–36). Springer Fachmedien Wiesbaden. https://link.springer.com/10.1007/978-3-658-36179-2_3

• Himelboim, I. (2017). Social Network Analysis (Social Media) (J. Matthes, C. S. Davis, & R. F. Potter, Eds.; 1st ed., pp. 1–15). Wiley. https://onlinelibrary.wiley.com/doi/10.1002/9781118901731.iecrm0236

• Maier, D., Waldherr, A., Miltner, P., Wiedemann, G., Niekler, A., Keinert, A., Pfetsch, B., Heyer, G., Reber, U., Häussler, T., Schmid-Petri, H., & Adam, S. (2018). Applying LDA Topic Modeling in Communication Research: Toward a Valid and Reliable Methodology. Communication Methods and Measures, 12(2-3), 93–118. https://doi.org/10.1080/19312458.2018.1430754

Topic modeling in R

• Atteveldt, W. van, Trilling, D., & Arcíla, C. (2021). Computational analysis of communication: A practical introduction to the analysis of texts, networks, and images with code examples in python and r. John Wiley & Sons.

• Silge, J., & Hvitfeldt, E. (n.d.). Supervised machine learning for text analysis in r. https://smltar.com/

• Silge, J., & Robinson, D. (2017). Text mining with r: A tidy approach (First edition). O’Reilly.

• Welbers, K., Van Atteveldt, W., & Benoit, K. (2017). Text Analysis in R. Communication Methods and Measures, 11(4), 245–265. https://doi.org/10.1080/19312458.2017.1387238

Useful resources

• Tutorials des CCS-Amsterdam zu “quanteda-based” Textanalyse:
  • 📖 Text analysis (including 🎥 video tutorial)
  • 📖 Lexical sentiment analysis (including 🎥 video tutorial)
  • 📖 LDA Topic Modeling (including 🎥 video tutorial)
  • 📖 Structural Topic Modeling (including 🎥 video tutorial)

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