π Community Detection in Spatial Networks - a Systematic Literature Overview
π Publish year: 2025
π§βπ»Authors: CΒ΄atia S. N. Sepetauskas, Giovanni G. Soares, Felipe O. Simoyama, ...
π’Universities: National Institute for Space Research (INPE) & University of SΛao Paulo (USP) & State University of Bahia (UNEB), Brazil
π Study the paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #community_detection #spatial
π Publish year: 2025
π§βπ»Authors: CΒ΄atia S. N. Sepetauskas, Giovanni G. Soares, Felipe O. Simoyama, ...
π’Universities: National Institute for Space Research (INPE) & University of SΛao Paulo (USP) & State University of Bahia (UNEB), Brazil
π Study the paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #community_detection #spatial
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π Social network analysis in agricultural economics: progress, challenges and prospects of an integrated methodology
π Journal: China Agricultural Economic Review (I.F.=5.6 - Q1)
π Publish year: 2025
π§βπ»Authors: Rui Mao, Yu Gan, Xiaohua Yu
π’University: Zhejiang University, China - University of Gottingen, Germany
π Study the paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #agriculture #economics
π Journal: China Agricultural Economic Review (I.F.=5.6 - Q1)
π Publish year: 2025
π§βπ»Authors: Rui Mao, Yu Gan, Xiaohua Yu
π’University: Zhejiang University, China - University of Gottingen, Germany
π Study the paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #agriculture #economics
π1
π½ Graph Embedding in practice
π Watch part 1
π Watch part 2
β‘οΈChannel: @ComplexNetworkAnalysis
#video #emebdding
π Watch part 1
π Watch part 2
β‘οΈChannel: @ComplexNetworkAnalysis
#video #emebdding
YouTube
Mining Complex Networks - Chapter 6 (part 1/2) - Graph Embeddings
@MiningComplexNetworks
π1
September 5, 2025
NodeXL Academy offers a free 90 minute virtual event to demonstrate the use of NodeXL for teaching networks and social media analysis. No coding required. If you can make a pie chart you can now make a network chart in with NodeXL. Gain quick insights into the influencers and. Market segmentation in a social media discussion stream. Automated analysis and visualizations that are published as a web based interactive dashboard. See: https://smrfoundation.org
Free ebook: https://nodexl.com/shop
Sample dashboard:
https://app.powerbi.com/view?r=eyJrIjoiNzZlN2EwNTYtNGUwMS00NmZhLTgyOGEtNjZiZmVmOTllYzNlIiwidCI6IjI5ZDRjMTFjLTA1N2MtNDg3Zi04ZmRhLWU4NmQ1OTkzOWU2NCIsImMiOjZ9
NodeXL Academy offers a free 90 minute virtual event to demonstrate the use of NodeXL for teaching networks and social media analysis. No coding required. If you can make a pie chart you can now make a network chart in with NodeXL. Gain quick insights into the influencers and. Market segmentation in a social media discussion stream. Automated analysis and visualizations that are published as a web based interactive dashboard. See: https://smrfoundation.org
Free ebook: https://nodexl.com/shop
Sample dashboard:
https://app.powerbi.com/view?r=eyJrIjoiNzZlN2EwNTYtNGUwMS00NmZhLTgyOGEtNjZiZmVmOTllYzNlIiwidCI6IjI5ZDRjMTFjLTA1N2MtNDg3Zi04ZmRhLWU4NmQ1OTkzOWU2NCIsImMiOjZ9
www.smrfoundation.org
The home of NodeXL | Your Social Network Analysis Tool for Social Media
The SMR Foundation supports social network analysis (SNA) tools that enable the collection, analysis and visualization of social media data.
π1
π Pattern detection in bipartite networks: A review of terminology, applications, and methods
π Publish year: 2024
πJournal: PLOS Complex Systems
π§βπ»Authors: Zachary P. Neal,Annabell Cadieux,Diego Garlaschelli,...
π’Universities: Michigan State University & University of Vermont & Arizona State University, , USA - Halle, Germany - Leiden University, Italy
π Study paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #bipartite
π Publish year: 2024
πJournal: PLOS Complex Systems
π§βπ»Authors: Zachary P. Neal,Annabell Cadieux,Diego Garlaschelli,...
π’Universities: Michigan State University & University of Vermont & Arizona State University, , USA - Halle, Germany - Leiden University, Italy
π Study paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #bipartite
π1
πSystematic Review of Graph Neural Network for Malicious Attack Detection
π Publish year: 2025
πJournal: Information (I.F=2.9 )
π§βπ»Authors: Sarah Mohammed Alshehri , Sanaa Abdullah Sharaf and Rania Abdullrahman Molla
π’Universities: King Abdulaziz University, Jeddah 21589, Saudi Arabia.
π Study paper
π±Channel: @ComplexNetworkAnalysis
#paper #GNN #Malicious #Attack #review
π Publish year: 2025
πJournal: Information (I.F=2.9 )
π§βπ»Authors: Sarah Mohammed Alshehri , Sanaa Abdullah Sharaf and Rania Abdullrahman Molla
π’Universities: King Abdulaziz University, Jeddah 21589, Saudi Arabia.
π Study paper
π±Channel: @ComplexNetworkAnalysis
#paper #GNN #Malicious #Attack #review
π1
πΉ Introduction to Graph Machine Learning: Methods and Applications
π₯ Jundong Li, Associate Professor, University of Virginia
π Watch
β‘οΈChannel: @ComplexNetworkAnalysis
#video #graph_machine_learning
π₯ Jundong Li, Associate Professor, University of Virginia
π Watch
β‘οΈChannel: @ComplexNetworkAnalysis
#video #graph_machine_learning
YouTube
Introduction to Graph Machine Learning: Methods and Applications
To get the slides and a certificate of completion, go to https://academy.isdsa.org/moodle/course/view.php?id=26
Graph-structured data is central to many real-world problems, encompassing domains such as recommender systems, social network analysis, and computationalβ¦
Graph-structured data is central to many real-world problems, encompassing domains such as recommender systems, social network analysis, and computationalβ¦
π2
π Visibility graph analysis for educational data
π Publish year: 2025
πJournal: Scientific Reports (I.F. = 3.2)
π§βπ»Authors: Hadis Azizi, Mohammad Sadra Amini, Sadegh Sulaimany & Aso Mafakheri
π’University: Social and Biological Network Analysis Laboratory (SBNA), University of Kurdistan, Iran
π Study paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #educational_data #visibility_graph
π Publish year: 2025
πJournal: Scientific Reports (I.F. = 3.2)
π§βπ»Authors: Hadis Azizi, Mohammad Sadra Amini, Sadegh Sulaimany & Aso Mafakheri
π’University: Social and Biological Network Analysis Laboratory (SBNA), University of Kurdistan, Iran
π Study paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #educational_data #visibility_graph
π2β€1π₯1
π Interpretable graph-based models on multimodal biomedical data integration: A technical review and benchmarking
π Publish year: 2025
π§βπ»Authors: Alireza Sadeghi, Farshid Hajati, Ahmadreza Argha, ...
π’Universities: Clemson University, USA - University of New England & UNSW Sydney, Australia - Chinese Academy of Sciences, China.
π Study paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #multimodal #biomedical #interpretable #graph_machine_learning #explainability
π Publish year: 2025
π§βπ»Authors: Alireza Sadeghi, Farshid Hajati, Ahmadreza Argha, ...
π’Universities: Clemson University, USA - University of New England & UNSW Sydney, Australia - Chinese Academy of Sciences, China.
π Study paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #multimodal #biomedical #interpretable #graph_machine_learning #explainability
π2
π A Survey of Link Prediction in Temporal Networks
π Publish year: 2025
π§βπ»Authors: Jiafeng Xiong, Ahmad Zareie and Rizos Sakellariou
π’Universities: University of Manchester & University of Sheffield, UK
π Study paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #link_prediction #temporal
π Publish year: 2025
π§βπ»Authors: Jiafeng Xiong, Ahmad Zareie and Rizos Sakellariou
π’Universities: University of Manchester & University of Sheffield, UK
π Study paper
β‘οΈChannel: @ComplexNetworkAnalysis
#review #link_prediction #temporal
π2
πΉ Mathematical Models of Social Connectivity: The Role of Transitivity and Clustering
π Watch
β‘οΈChannel: @ComplexNetworkAnalysis
#video #clustering_coefficeint #transitivity
π Watch
β‘οΈChannel: @ComplexNetworkAnalysis
#video #clustering_coefficeint #transitivity
YouTube
Mathematical Models of Social Connectivity: The Role of Transitivity and Clustering
This lecture explains the fundamental concepts of transitivity, global and local clustering coefficients, and structural holes in social network analysis. Using intuitive explanations and practical social media examples, the video explains how these measuresβ¦