MAIS-202-Final-Project: Topic Modeling Using LDA

Theory Notes:

This is a file that contains (messy) notes on the theory behind topic modeling and LDA

References:

“Introduction to Latent Dirichlet Allocation.” Edwin Chens Blog Atom, https://blog.echen.me/2011/08/22/introduction-to-latent-dirichlet-allocation/.

“Holistic Sentiment Analysis across Languages, Part I: LDA.” N. Saphra Misunderstands NLP Papers, http://confusedlanguagetech.blogspot.com/2012/07/jordan-boyd-graber-and-philip-resnik.html.

Kapadia, Shashank. “Topic Modeling in Python: Latent Dirichlet Allocation (LDA).” Medium, Towards Data Science, 23 Dec. 2022, https://towardsdatascience.com/end-to-end-topic-modeling-in-python-latent-dirichlet-allocation-lda-35ce4ed6b3e0.

Rajeev, Malvika. “Using LDA to Find Trends in ML Papers.” Malvika R, Malvika R, 7 Sept. 2020, https://www.malvikarajeev.com/post/lda/.

Jelodar, Hamed, et al. “Latent Dirichlet Allocation (LDA) and Topic Modeling: Models, Applications, a Survey.” ArXiv.org, 6 Dec. 2018, https://arxiv.org/abs/1711.04305.