Appraising discrepancies and similarities in semantic networks using concept-centered subnetworks

Medeuov, Darkhan; Roth, Camille; Puzyreva, Kseniia; Basov, Nikita

doi:10.1007/s41109-021-00408-0

Cited by 4 publications

(2 citation statements)

References 16 publications

(16 reference statements)

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“…Second, we need an approach that allows us to estimate the extent of individual variations in lexical networks. Third, in educational applications simple enough methods for text analysis are needed because advanced methods of text analysis [8][9][10][11] require expertise and are thus not likely to be adopted.…”

Section: Introductionmentioning

confidence: 99%

Lexical Networks Constructed to Correspond to Students’ Short Written Responses: A Quantum Semantic Approach

Koponen

Södervik

Nousiainen

2023

Complex Networks and Their Applications XI

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A simple method to construct lexical networks (lexicons) of how students use scientific terms in written texts is introduced. The method is based on a recently introduced quantum semantics generalization of a word-pair cooccurrence. Quantum semantics allows entangled co-occurrence, thus allowing to model the effect of subjective bias on weighting the importance of word cooccurrence. Using such a generalized word-pair co-occurrence counting, we construct students' lexicons of scientific (life-science) terms they use in their written responses to questions concerning food chains in life-science contexts. The method allows us to construct ensembles of lexicons that probabilistically simulate the variability of individual lexicons. The re-analyses of the written reports show that while sets of top-ranking terms contain nearly the same terms irrespective of details of the method used to count co-occurrences, the relative rankings of some key-terms may be different in quantum semantic analysis.

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Section: Introductionmentioning

confidence: 99%

Lexical Networks Constructed to Correspond to Students’ Short Written Responses: A Quantum Semantic Approach

Koponen

Södervik

Nousiainen

2023

Complex Networks and Their Applications XI

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“…The co-word mapping methods capture syntactic structures only up to word adjacency, but they can be generalized to take into account more complicated syntactic structures composed of subject–verb–object triads and networks constituted by such triads [ 31 ]. Other methods going beyond co-word analysis are looking in detail for example: concept diversity (cognitive content) through lexical diversity of text [ 14 ]; relation of key concepts and the architecture of the text structure [ 32 , 33 ]; searching semantic frames through finding communities of verbs and their arguments [ 34 ]; creating semantic networks by using concept-centered sub-networks [ 35 ]; and finding the larger-scale semantic structure of texts [ 36 , 37 ]. In all these cases, complex networks methods are used in construction of the semantic, lexical, or concept networks, and different network measures (closeness centrality, betweenness centrality, or some specially engineered measures for network topology) are utilized in analysis.…”

Section: Introductionmentioning

confidence: 99%

Lexicons of Key Terms in Scholarly Texts and Their Disciplinary Differences: From Quantum Semantics Construction to Relative-Entropy-Based Comparisons

Koponen

Södervik

2022

Entropy

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Complex networks are often used to analyze written text and reports by rendering texts in the form of a semantic network, forming a lexicon of words or key terms. Many existing methods to construct lexicons are based on counting word co-occurrences, having the advantage of simplicity and ease of applicability. Here, we use a quantum semantics approach to generalize such methods, allowing us to model the entanglement of terms and words. We show how quantum semantics can be applied to reveal disciplinary differences in the use of key terms by analyzing 12 scholarly texts that represent the different positions of various disciplinary schools (of conceptual change research) on the same topic (conceptual change). In addition, attention is paid to how closely the lexicons corresponding to different positions can be brought into agreement by suitable tuning of the entanglement factors. In comparing the lexicons, we invoke complex network-based analysis based on exponential matrix transformation and use information theoretic relative entropy (Jensen–Shannon divergence) as the operationalization of differences between lexicons. The results suggest that quantum semantics is a viable way to model the disciplinary differences of lexicons and how they can be tuned for a better agreement.

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Systematic review of the “semantic network” definitions

Pereira¹,

Grilo²,

Fadigas³

et al. 2022

Expert Systems with Applications

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Appraising discrepancies and similarities in semantic networks using concept-centered subnetworks

Cited by 4 publications

References 16 publications

Lexical Networks Constructed to Correspond to Students’ Short Written Responses: A Quantum Semantic Approach

Lexical Networks Constructed to Correspond to Students’ Short Written Responses: A Quantum Semantic Approach

Lexicons of Key Terms in Scholarly Texts and Their Disciplinary Differences: From Quantum Semantics Construction to Relative-Entropy-Based Comparisons

Systematic review of the “semantic network” definitions

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