mlsanityData to 7 Oct 2026

Determination of the Number of Topics Intrinsically: Is It Possible?

arXiv 2406.10402 ↗First posted 14 Jun 2024cs.CL cs.IR math.PRcited by 3

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Abstract (arXiv)

The number of topics might be the most important parameter of a topic model. The topic modelling community has developed a set of various procedures to estimate the number of topics in a dataset, but there has not yet been a sufficiently complete comparison of existing practices. This study attempts to partially fill this gap by investigating the performance of various methods applied to several topic models on a number of publicly available corpora. Further analysis demonstrates that intrinsic methods are far from being reliable and accurate tools. The number of topics is shown to be a method- and a model-dependent quantity, as opposed to being an absolute property of a particular corpus. We conclude that other methods for dealing with this problem should be developed and suggest some promising directions for further research.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 11 of its 48 references that are in the map. First posted on arXiv 14 Jun 2024.

Builds on

11 of 48 references.

References · 11

  1. 2013Probabilistic Latent Semantic Analysiscited by 63
  2. 2017A network approach to topic modelscited by 25
  3. 2014How Many Topics? Stability Analysis for Topic Modelscited by 16
  4. 2016What is Wrong with Topic Modeling? (and How to Fix it Using Search-based Software Engineering)cited by 14
  5. 2017Stability of Topic Modeling via Matrix Factorizationcited by 13
  6. 2018Measuring LDA Topic Stability from Clusters of Replicated Runscited by 6
  7. 2017Fuzzy Approach Topic Discovery in Health and Medical Corporacited by 5
  8. 2014Parsimonious Topic Models with Salient Word Discoverycited by 2
  9. 2017Prior matters: simple and general methods for evaluating and improving topic quality in topic modelingcited by 2
  10. 2018Application of R'enyi and Tsallis Entropies to Topic Modeling Optimizationcited by 2
  11. 2014"Look Ma, No Hands!" A Parameter-Free Topic Modelcited by 1

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Citing papers per year: 2024: 1; 2025: 2.

3 papers.