Microscopic network measures as indicators of sentence-level integration during reading¶
Research Method · All research methods
Evidence · 3 claims (3 for) · 1 study (1 associational),q3· 1 of 1 report an effect size · 3 claims rest on one study
Description¶
The article frames reading networks with sentences as nodes and transitions between sentences as weighted edges, and proposes four microscopic measures of integration. "Strength refers to the number of edges connected to a node" and reflects how much a sentence has been visited; betweenness identifies sentences lying on shortest paths between others; harmonic centrality (a form of closeness centrality) quantifies proximity to all other sentences; and the local clustering coefficient captures interconnection among a sentence's neighbors. The approach aligns with construction-integration accounts of mental representation building.
Accounts¶
- Microscopic network measures as indicators of sentence-level integration during reading: The article frames reading networks with sentences as nodes and transitions between sentences as weighted edges, and proposes four microscopic measures of integration. "Strength refers to the number of edges connected to a node" and reflects how much a sentence has been visited; betweenness identifies sentences lying on shortest paths between others; harmonic centrality (a form of closeness centrality) quantifies proximity to all other sentences; and the local clustering coefficient captures interconnection among a sentence's neighbors. The approach aligns with construction-integration accounts of mental representation building. (Catrysse et al. (2025))
Claims¶
- Strength is strongly positively correlated with second-pass reading time, while betweenness, harmonic centrality and local clustering coefficient are not related to duration measures [+M]
- Readers with higher working memory capacity make more transitions between sentences (higher strength) [+M]
- Topic-medial sentences have higher strength than topic-initial and topic-final sentences [+M]
Related Research Methods¶
Key Sources¶
- Catrysse, L., van Daal, T., Jarodzka, H., Kaakinen, J. K., Donche, V., & Gijbels, D. (2025). How Eye Read: A Social Network Approach. Educational Psychology Review. https://doi.org/10.1007/s10648-025-10000-y
Page metadata
| Field | Value |
|---|---|
type |
research-method |
id |
microscopic-network-measures-as-indicators-of-sentence-level-integration-during-reading |
title |
Microscopic network measures as indicators of sentence-level integration during reading |
description |
The article frames reading networks with sentences as nodes and transitions between sentences as weighted edges, and proposes four microscopic measures of integration. |
status |
review |
generated |
by process:settle-candidates on 2026-10-20 |
trust |
unverified — no one has confirmed this page's content |
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