ArticleEntropy (Basel, Switzerland)2018
Distance Entropy Cartography Characterises Centrality in Complex Networks.
Article in Entropy (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Optimization Method for Robustness of Hypernetwork Communication with Integrated Structural Features.Entropy (Basel, Switzerland) · 2026Article
- Cognitive modelling of concepts in the mental lexicon with multilayer networks: Insights, advancements, and future challenges.Psychonomic bulletin & review · 2024Review
- A Survey of Information Entropy Metrics for Complex Networks.Entropy (Basel, Switzerland) · 2020Review
- A Path-Based Distribution Measure for Network Comparison.Entropy (Basel, Switzerland) · 2020Article
- Forma mentis networks map how nursing and engineering students enhance their mindsets about innovation and health during professional growth.PeerJ. Computer science · 2020Article
- The multiplex structure of the mental lexicon influences picture naming in people with aphasia.Journal of complex networks · 2019Article
- Finite-Time Synchronization of Markovian Jumping Complex Networks with Non-Identical Nodes and Impulsive Effects.Entropy (Basel, Switzerland) · 2019Article
- Characterizing Complex Networks Using Entropy-Degree Diagrams: Unveiling Changes in Functional Brain Connectivity Induced by Ayahuasca.Entropy (Basel, Switzerland) · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We introduce distance entropy as a measure of homogeneity in the distribution of path lengths between a given node and its neighbours in a complex network. Distance entropy defines a new centrality measure whose properties are investigated for a variety of synthetic network models. By coupling distance entropy information with closeness centrality, we introduce a network cartography which allows one to reduce the degeneracy of ranking based on closeness alone. We apply this methodology to the empirical multiplex lexical network encoding the linguistic relationships known to English speaking toddlers. We show that the distance entropy cartography better predicts how children learn words compared to closeness centrality. Our results highlight the importance of distance entropy for gaining insights from distance patterns in complex networks.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.