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πŸ“‘Clustering and link prediction for mesoscopic COVID-19 transmission networks in Republic of Korea

πŸ“˜journal: ChaosI.F=3.436)
πŸ—“Publish year: 2023

πŸ“Ž Study the paper

πŸ“²Channel: @ComplexNetworkAnalysis
#paper #COVID_19 #link_prediction #Clustering
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πŸ“‘Degree Centrality, Betweenness Centrality, and Closeness Centrality in Social Network

πŸ“˜Conference: Proceedings of the 2017 2nd International Conference on Modelling, Simulation and Applied Mathematics (MSAM2017)

πŸ’₯Social network theory is becoming more and more significant in social science, and the centrality measure is underlying this burgeoning theory. In perspective of social network, individuals, organizations, companies etc. are like nodes in the network, and centrality is used to measure these nodes’ power, activity, communication convenience and so on. Meanwhile, degree centrality, betweenness centrality and closeness centrality are the popular detailed measurements. Thispaper presents these 3 centrality in-depth, from principle to algorithm, and prospect good in the future use.

πŸ—“Publish year: 2017

πŸ“Ž Study the paper

πŸ“²Channel: @ComplexNetworkAnalysis
#paper #Centrality #Social_Network #Clustering
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πŸ“„A Survey of Link Prediction Techniques

πŸ—“Publish year: 2023

πŸ“ŽStudy paper

πŸ“±Channel: @ComplexNetworkAnalysis
#paper #Link_Predictionc #Techniques #Survey
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πŸ“„Structure and function of complex brain networks

πŸ“˜Journal: Dialogues in Clinical Neuroscience (DCNS)

πŸ“ŽStudy paper

πŸ“±Channel: @ComplexNetworkAnalysis
#paper #Structure #function #complex #brain #networks
πŸ“‘A Survey on Studying the Social Networks of Students

πŸ—“Publish year: 2019

πŸ“Ž Study the paper

πŸ“²Channel: @ComplexNetworkAnalysis
#paper #Social_Networks #Survey
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🎞 Social Network Analysis Methods for Network Building and Impact

πŸ’₯Free recorded session about social network analysis method

πŸ’₯This session will discuss the social network analysis methodology and how it can be applied and leveraged in fellowships and with alumni networks for multiple benefits.

πŸ“½ Watch

πŸ“±Channel: @ComplexNetworkAnalysis

#video #Methods #Network_Building #Impact
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πŸ“„Centrality measures in fuzzy social networks

πŸ“˜journal: Information systems (l.F=7.767)
πŸ—“Publish year: 2023

πŸ“Ž Study the paper

πŸ“²Channel: @ComplexNetworkAnalysis
#paper #social_network #fuzzy #Centrality
2020_Applications_of_link_prediction_in_social_networks_A_review.pdf
2.4 MB
πŸ“„Applications of link prediction in social networks: A review

πŸ“˜journal: Journal of Network and Computer Applications (I.F=8.7)
πŸ—“Publish year: 2020

πŸ“ŽStudy paper

πŸ“±Channel: @ComplexNetworkAnalysis
#paper #Applications #link_prediction #review
πŸ“„Influence maximization on temporal
networks: a review

πŸ—“Publish year: 2023

πŸ“ŽStudy paper

πŸ“±Channel: @ComplexNetworkAnalysis
#paper #Influence #maximization #temporal_networks #review
2020_A_survey_on_network_node_ranking_algorithms_Representative.pdf
793.4 KB
πŸ“„A survey on network node ranking algorithms: Representative methods, extensions, and applications

πŸ“˜journal: Science China Technological Sciences(I.F= 4.6)
πŸ—“Publish year: 2020

πŸ“ŽStudy paper

πŸ“±Channel: @ComplexNetworkAnalysis
#paper #network #node #ranking #algorithms #Representative #methods #extensions #applications #survey
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πŸ“„Python modularity Examples

πŸ’₯Technical paper

🌐 Study

πŸ“²Channel: @ComplexNetworkAnalysis

#paper #Graph #code #python #modularity
πŸ“„Network Analysis Based on Important Node Selection and Community Detection

πŸ“˜journal: MATHEMATICS-BASEL(I.F= 2.4)
πŸ—“Publish year: 2021

πŸ“ŽStudy paper

πŸ“±Channel: @ComplexNetworkAnalysis
#paper #Important_Nodes #Community_Detection
πŸ“„Community Detection

πŸ’₯Technical paper
 
🌐 Study 

πŸ“²Channel: @ComplexNetworkAnalysis

#paper #Graph #code #python #Community_Detection
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πŸ“„A Mini Review of Node Centrality Metrics in Biological Networks

πŸ“˜journal: International Journal of Network Dynamics and Intelligence (IJNDI)
πŸ—“Publish year: 2022

πŸ“ŽStudy paper

πŸ“±Channel: @ComplexNetworkAnalysis
#paper #Node_Centrality #Metrics #Biological_Network #Mini_Review
πŸ“„Identifying spreading influence nodes for social networks

πŸ“˜journal: Frontiers of Engineering Management (FEM)(I.F=7.4)
πŸ—“Publish year: 2022

πŸ“ŽStudy paper

πŸ“±Channel: @ComplexNetworkAnalysis
#paper #Identifying #spreading #influence_nodes
πŸ“„A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection

πŸ—“Publish year: 2021

πŸ“Ž Study the paper

πŸ“²Channel: @ComplexNetworkAnalysis
#paper #GNN #Survey #Neural_Network #Forecasting #Anomaly_Detection
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🎞 Social Network Analysis - network structure
πŸ’₯Free recorded lecture from UCCSS (University of California Computational Social Sciences)

πŸ”ΉThis lecture is part of the University of California wide online course on Computational Social Science (UCCSS), produced with input from Professors from all 10 UC campuses and offered to UC students for credit since 2018. For more on this topic, see the open Online Specialization link
.

πŸ“½ Watch

πŸ’»Open Online Specialization

πŸ“±Channel: @ComplexNetworkAnalysis

#video #network_structure
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πŸ“„Construction of Knowledge Graphs: Current State and Challenges

πŸ—“Publish year: 2023

πŸ“Ž Study the paper

πŸ“²Channel: @ComplexNetworkAnalysis
#paper #Knowledge_Graph
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πŸ“„Fairness-Aware Graph Neural Networks: A Survey

πŸ—“Publish year: 2023

πŸ“ŽStudy paper

πŸ“±Channel: @ComplexNetworkAnalysis
#paper #Fairness #Graph_Neural_Networks #survey
🎞 Machine Learning with Graphs: Reasoning in Knowledge Graphs, Answering Predictive Queries, Query2box: Reasoning over KGs

πŸ’₯Free recorded course by Jure Leskovec, Computer Science, PhD

πŸ’₯ IIn this lecture, we introduce how to perform reasoning over knowledge graphs and provide answers to complex queries. We talk about different possible queries that one can get over a knowledge graph, and how to answer them by traversing over the graph. We also show how incompleteness of knowledge graphs can limit our ability to provide complete answers. We finally talk about how we can solve this problem by generalizing the link prediction task.

πŸ“½ Watch: part1 part2 part3

πŸ“ slide

πŸ“²Channel: @ComplexNetworkAnalysis

#video #course #Graph #Machine_Learning #Knowledge_Graph
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πŸ“„Construction of Knowledge Graphs: Current State and Challenges

πŸ—“Publish year: 2023

πŸ“ŽStudy paper

πŸ“±Channel: @ComplexNetworkAnalysis
#paper #Knowledge_Graph #Current_State
#Challenges
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