arbiter
JournalsPricingAccount

Untangling orientations and dynamics of science–technology interactions through a community-based linkage approach

Y.S. Zhang et al.

Journal of Information Science2026https://doi.org/10.1177/01655515251403534article
AJG 2
Weight
0.50

What the paper says

While many studies have investigated science and technology (S&T) interaction, the fine-grained interaction patterns at the structural level remain unclear. This study proposes a novel community-based linkage approach to elucidate the orientations and dynamics of S&T community interactions. We establish S&T community linkages through network modelling and community detection algorithms, and then quantify the interaction strength, direction and dynamics between different S&T communities. Through an analysis of 790,000 academic publications and 140,000 patents in the artificial intelligence (AI) domain, we find that S&T interaction in this field has continuously strengthened over time. By exploring the structural conditions under which strong S&T community linkages occur, we discover that intensive S&T interactions are more likely to happen within communities of similar size or density. Furthermore, fine-grained differences exist in the science drives technology and technology drives science modalities within AI. This study provides new insights into potential patterns of S&T interaction from a community-linkage structural perspective.

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.1177/01655515251403534

Or copy a formatted citation

@article{y.s.2026,
  title        = {{Untangling orientations and dynamics of science–technology interactions through a community-based linkage approach}},
  author       = {Y.S. Zhang et al.},
  journal      = {Journal of Information Science},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/01655515251403534},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Untangling orientations and dynamics of science–technology interactions through a community-based linkage approach

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.