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Bayesiansk netværksdiffusionsanalyse

Bayesiansk netværksdiffusionsanalyse anvender Bayesiansk probabilistisk inferens til studiet af, hvordan information, sygdomme, adfærd eller innovationer forplanter sig gennem et netværk. Ved at placere prioris over diffusionsparametre og opdatere dem med observerede kaskadedata kvantificeres transmissionsrater, identificeres indflydelsesrige spredere, rekonstrueres latente propagationsveje, og der gives fulde usikkerhedsestimater – alt sammen inden for et principielt statistisk rammeværk.

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Kilder

  1. Gomez Rodriguez, M., Leskovec, J., & Scholkopf, B. (2012). Structure and Dynamics of Information Pathways in Online Media. Proceedings of the 6th ACM International Conference on Web Search and Data Mining (WSDM), 23–32. DOI: 10.1145/2433396.2433402
  2. Kitsak, M., Gallos, L. K., Havlin, S., Liljeros, F., Muchnik, L., Stanley, H. E., & Makse, H. A. (2010). Identification of influential spreaders in complex networks. Nature Physics, 6(11), 888–893. DOI: 10.1038/nphys1746

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ScholarGate. (2026, June 3). Bayesian Network Diffusion Analysis (Probabilistic Inference on Contagion and Spreading Processes). ScholarGate. https://scholargate.app/da/network-analysis/bayesian-network-diffusion-analysis

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ScholarGateBayesian Network Diffusion Analysis (Bayesian Network Diffusion Analysis (Probabilistic Inference on Contagion and Spreading Processes)). Hentet 2026-06-15 fra https://scholargate.app/da/network-analysis/bayesian-network-diffusion-analysis · Datasæt: https://doi.org/10.5281/zenodo.20539026