mlsanityData to 7 Oct 2026

Term-community-based topic detection with variable resolution

arXiv 2103.13550 ↗First posted 25 Mar 2021cs.CLcited by 1

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Abstract (arXiv)

Network-based procedures for topic detection in huge text collections offer an intuitive alternative to probabilistic topic models. We present in detail a method that is especially designed with the requirements of domain experts in mind. Like similar methods, it employs community detection in term co-occurrence graphs, but it is enhanced by including a resolution parameter that can be used for changing the targeted topic granularity. We also establish a term ranking and use semantic word-embedding for presenting term communities in a way that facilitates their interpretation. We demonstrate the application of our method with a widely used corpus of general news articles and show the results of detailed social-sciences expert evaluations of detected topics at various resolutions. A comparison with topics detected by Latent Dirichlet Allocation is also included. Finally, we discuss factors that influence topic interpretation.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 15 of its 80 references that are in the map. First posted on arXiv 25 Mar 2021.

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15 of 80 references.

References · 15

  1. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,346
  2. 2016Enriching Word Vectors with Subword Informationcited by 1,578
  3. 2020A Survey on Knowledge Graphs: Representation, Acquisition and Applicationscited by 643
  4. 2018From Louvain to Leiden: guaranteeing well-connected communitiescited by 379
  5. 2016Community detection in networks: A user guidecited by 105
  6. 2017Latent Dirichlet Allocation (LDA) and Topic modeling: models, applications, a surveycited by 90
  7. 2017A network approach to topic modelscited by 25
  8. 2016Community detection in networks: Modularity optimization and maximum likelihood are equivalentcited by 10
  9. 2014A high-reproducibility and high-accuracy method for automated topic classificationcited by 6
  10. 2017From Image to Text Classification: A Novel Approach based on Clustering Word Embeddingscited by 6
  11. 2015Co-word Maps and Topic Modeling: A Comparison Using Small and Medium-Sized Corpora (n < 1000)cited by 5
  12. 2019Consistency of community structure in complex networkscited by 4
3 more
  1. 2015Topic segmentation via community detection in complex networkscited by 3
  2. 2019The Power of Communities: A Text Classification Model with Automated Labeling Process Using Network Community Detectioncited by 1
  3. 2021TeCoMiner: Topic Discovery Through Term Community Detectioncited by 1

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