Topological Analysis of Syntactic Structures
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Abstract (arXiv)
We use the persistent homology method of topological data analysis and dimensional analysis techniques to study data of syntactic structures of world languages. We analyze relations between syntactic parameters in terms of dimensionality, of hierarchical clustering structures, and of non-trivial loops. We show there are relations that hold across language families and additional relations that are family-specific. We then analyze the trees describing the merging structure of persistent connected components for languages in different language families and we show that they partly correlate to historical phylogenetic trees but with significant differences. We also show the existence of interesting non-trivial persistent first homology groups in various language families. We give examples where explicit generators for the persistent first homology can be identified, some of which appear to correspond to homoplasy phenomena, while others may have an explanation in terms of historical linguistics, corresponding to known cases of syntactic borrowing across different language subfamilies.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Mar 2019.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 3; 2024: 2; 2025: 0; 2026: 1.
9 papers.
- 2023Mathematical Structure of Syntactic Mergecited by 17
- 2023TOPFORMER: Topology-Aware Authorship Attribution of Deepfake Texts with Diverse Writing Stylescited by 10
- 2022Natural Language Syntax Complies with the Free-Energy Principlecited by 7
- 2021Topos and Stacks of Deep Neural Networkscited by 5
- 2023Image Classification using Combination of Topological Features and Neural Networkscited by 2
- 2024Topological Data Analysis Applications in Natural Language Processing: A Surveycited by 2
- 2021Syntactic structures and the general Markov modelscited by 1
- 2024Linguistics from a topological viewpointcited by 1
- 2026Optimizing Soft Prompt Tuning via Structural Evolutioncited by 0
- 2026Optimizing Soft Prompt Tuning via Structural Evolution18 Feb 2026
- 2024Topological Data Analysis Applications in Natural Language Processing: A Survey15 Nov 2024
- 2024Linguistics from a topological viewpoint16 Mar 2024
- 2023Image Classification using Combination of Topological Features and Neural Networks10 Nov 2023
- 2023TOPFORMER: Topology-Aware Authorship Attribution of Deepfake Texts with Diverse Writing Styles22 Sep 2023
- 2023Mathematical Structure of Syntactic Merge29 May 2023
- 2022Natural Language Syntax Complies with the Free-Energy Principle27 Oct 2022
- 2021Topos and Stacks of Deep Neural Networks28 Jun 2021
- 2021Syntactic structures and the general Markov models17 Apr 2021