Network Analysis Resources & Updates – Telegram
Network Analysis Resources & Updates
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📑 Knowledge Graphs

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Journal: ACM Computing Surveys(I.F.=14.324)
🗓Publish year: 2021

📎 Study the paper

📲Channel: @ComplexNetworkAnalysis
#paper #Survey #Knowledge_Graphs
🔥2
2021_Graph_Signal_Processing,_Graph_Neural_Network_and_Graph_Learning.pdf
3.9 MB
📄Graph Signal Processing, Graph Neural Network and Graph Learning on Biological Data: A Systematic Review

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Journal: IEEE REVIEWS IN BIOMEDICAL ENGINEERING (I.F=7.073)
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Publish year: 2021

📎Study paper

📱Channel: @ComplexNetworkAnalysis
#paper #Graph_Signal_Processing #Graph_Neural_Network #Graph_Learning #Biological #Review
📄Community Detection Algorithms in Healthcare Applications: A Systematic Review

📘
Journal: IEEE Access (I.F=3.476)
🗓
Publish year: 2023

📎Study paper

📱Channel: @ComplexNetworkAnalysis
#paper #Community_Detection #Healthcare #Applications #Review
🔥2
2019-A review Knowledge reasoning over knowledge graph.pdf
2.2 MB
📑 A review: Knowledge reasoning over knowledge graph

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Journal: ACM Computing Surveys(I.F.=8.665)
🗓Publish year: 2019

📎 Study the paper

📲Channel: @ComplexNetworkAnalysis
#paper #review #Knowledge_Graphs
👍2
📑 Structure and dynamics of core/periphery networks

📘Journal: Journal of Complex Networks(I.F.=1.984)
🗓Publish year: 2013

📎 Study the paper

📲Channel: @ComplexNetworkAnalysis
#paper #review #periphery_networks
🔥2👍1
📑 Exploring network structure, dynamics, and function using networkx

📘Conference: conference: Exploring network structure, dynamics, and function using NetworkX

📎 Study the paper

📲Channel: @ComplexNetworkAnalysis
#paper #networkx
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2020_Fraud_detection_A_systematic_literature_review_of_graph_based.pdf
1.4 MB
📄Fraud detection: A systematic literature review of graph-based anomaly detection approaches

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Journal: Decision Support Systems (I.F=6.969)
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Publish year: 2020

📎Study paper

📱Channel: @ComplexNetworkAnalysis
#paper #Fraud #Detection #Review #graph_based #anomaly
📄Knowledge Graphs: Opportunities and Challenges

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Journal: Artificial Intelligence Review (I.F=9.588)
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Publish year: 2023

📎Study paper

📱Channel: @ComplexNetworkAnalysis
#paper #Knowledge_Graphs #Opportunities #Challenges
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📄Programming Graphs in Python

💥Technical paper

🌐 Study

📲Channel: @ComplexNetworkAnalysis

#paper #Graph #code #python
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📄Counterfactual Learning on Graphs: A Survey

🗓Publish year: 2023

📎Study paper

📱Channel: @ComplexNetworkAnalysis
#paper #Counterfactual_Learning #Graphs #Survey
🎓A comparison of visualisation techniques for complex networks

📘Master’s Thesis in Computer Science Royal Institute of Technology

🗓Publish year: 2016

📎Study Thesis

📱Channel: @ComplexNetworkAnalysis

#Thesis #comparison #visualisation #techniques
📄Programming Graphs in Python

💥Technical paper

🌐 Study

📲Channel: @ComplexNetworkAnalysis

#paper #Graph #code #python
👍4
📄Basic and Advanced Network Visualization with Gephi

💥Technical paper

📘 PDF

💻 data

📲Channel: @ComplexNetworkAnalysis

#tools #Gephi
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📄 Literature review on the influence of social networks

📘Conference: The Fifth International Conference on Social Science
🗓Publish year: 2023

📎Study paper

📱Channel: @ComplexNetworkAnalysis
#paper #Literature #influence #review
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📕Networks, Crowds, and Markets:
Reasoning About a Highly Connected World

📝Authors: David Easley and Jon Kleinberg.

💥Networks, Crowds, and Markets combines different scientific perspectives in its approach to understanding networks and behavior. Drawing on ideas from economics, sociology, computing and information science, and applied mathematics, it describes the emerging field of study that is growing at the interface of all these areas, addressing fundamental questions about how the social, economic, and technological worlds are connected.

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publish year: 2010
📖
Study book

📲Channel: @ComplexNetworkAnalysis

#book #network
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📄 Considering weights in real social networks: A review

📘Journal: Frontiers in Physics (I.F=3.718)
🗓Publish year: 2023

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📱Channel: @ComplexNetworkAnalysis
#paper #Considering #weights #review
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📕Network visualization with R

💥This is a comprehensive tutorial on network visualization with R. It covers data input and formats, visualization basics, parameters and layouts for one-mode and bipartite graphs; dealing with multiplex links, interactive and animated visualization for longitudinal networks; and visualizing networks on geographic maps. To follow the tutorial, download the code and data below and use R and RStudio. You can also check out the most recent versions of all my tutorials here.

📘 PDF

💻 code

🌐 Read online

📲Channel: @ComplexNetworkAnalysis

#book #R #code
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📄 Influential nodes identification in complex networks: a comprehensive literature review

📘Journal: Beni-Suef University Journal of Basic and Applied Sciences
🗓Publish year: 2023

📎Study paper

📱Channel: @ComplexNetworkAnalysis
#paper #nfluential #nodes #comprehensive #review
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