Applying LDA Topic Modeling in Communication Research: Toward a Valid and Reliable Methodology

By Daniel Maier, Annie Waldherr, Peter Miltner, Gregor Wiedemann, Andreas Niekler, A. Keinert, Barbara Pfetsch, Gerhard Heyer, Ueli Reber, Thomas Häussler and 2 more. 2018

736 citations recorded by the source corpus.

Subfields: Artificial Intelligence, General Social Sciences

View Paper: https://www.semanticscholar.org/paper/4ca7b73c788231884f777631db5ce0d54d9db084

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Roman Egger
2. Joanne Yu

In General Social Sciences

1. Roman Egger
2. Joanne Yu

Citations in the corpus

• A Topic Modeling Comparison Between LDA, NMF, Top2Vec, and BERTopic to Demystify Twitter Posts (2022, background): “Typically, documents contain mixed membership, which means that a mixture of topics exists in the corpus (Maier et al., 2018).”