Network Analysis Resources & Updates
3.09K subscribers
829 photos
163 files
1.14K links
Are you seeking assistance or eager to collaborate?
Don't hesitate to dispatch your insights, inquiries, proposals, promotions, bulletins, announcements, and more to our channel overseer. We're all ears!

Contact: @Questioner2
Download Telegram
πŸ“„Network and Graph Algorithms From Scratch

πŸ’₯Technical paper

🌐 Study

πŸ“²Channel: @ComplexNetworkAnalysis

#paper #Graph #code #python
2020_Statistical Network Analysis A Review.pdf
875.3 KB
πŸ“„Statistical Network Analysis: A Review with Applications to the Coronavirus Disease 2019 Pandemic

πŸ“˜
Journal: INTERNATIONAL STATISTICAL REVIEW (I.F=1.946)
πŸ—“
Publish year: 2020

πŸ“ŽStudy paper

πŸ“±Channel: @ComplexNetworkAnalysis
#paper #Application #Coronavirus #review
2021_A_survey_on_graph_based_methods_for_similarity_searches_in.pdf
1.6 MB
πŸ“„A survey on graph-based methods for similarity searches in metric spaces

πŸ“˜Journal: Information Systems(I.F=7.453)

πŸ—“Publish year: 2021

πŸ“²Channel: @ComplexNetworkAnalysis
#paper #survey #graph
Social_Network_Theory_in_Construction_Industry_A_Scientometric_Review.pdf
414.4 KB
πŸ“„Social Network Theory in Construction Industry: A Scientometric Review

πŸ“˜Conference: Recent Trends in Civil Engineering

πŸ—“Publish year: 2022

πŸ“ŽStudy paper

πŸ“²Channel: @ComplexNetworkAnalysis
#paper #Review #Social_Network
On Anomaly Detection in Graphs as Node Classification.pdf
467.2 KB
πŸ“„On Anomaly Detection in Graphs as Node Classification

πŸ“˜Conference: Big Data Management and Analysis for Cyber Physical Systems

πŸ—“Publish year: 2022

πŸ“ŽStudy paper

πŸ“²Channel: @ComplexNetworkAnalysis
#paper #graph
πŸ“„Graph Learning Approaches to Recommender Systems: A Review

πŸ“˜
Journal: Information Retrieval
πŸ—“
Publish year: 2020

πŸ“ŽStudy paper

πŸ“±Channel: @ComplexNetworkAnalysis
#paper #Recommender_Systems #Graph #review
πŸŽ‰1
🎞 Graph Theory: Nearest Neighbor Algorithm (NNA)

πŸ’₯Free recorded tutorial

πŸ”ΉThis tutorial is about Nearest neighbour algorithm, Travelling salesman problem, Heuristic, Hamiltonian path

πŸ“½ Watch

πŸ“²Channel: @ComplexNetworkAnalysis
#video #Graph
πŸ‘1
πŸ“„A Note on Graph-Based Nearest Neighbor Search

πŸ—“Publish year: 2020

πŸ“ŽStudy paper

πŸ“²Channel: @ComplexNetworkAnalysis
#paper #Graph
πŸ‘4
πŸ“„Network Analysis for the Digital Humanities: Principles, Problems, Extensions

πŸ“˜
Journal: ISIS
πŸ—“
Publish year: 2019

πŸ“ŽStudy paper

πŸ“±Channel: @ComplexNetworkAnalysis
#paper #Digital #Humanities #Principles #Problems #Extensions
πŸ“„Network analysis on political election; populist vs social emergent behaviour

πŸ—“Publish year: 2023

πŸ“ŽStudy paper

πŸ“²Channel: @ComplexNetworkAnalysis
#paper
2022_Knowledge_Graphs_A_Practical_Review_of_the_Research_Landscape.pdf
510 KB
πŸ“„Knowledge Graphs: A Practical Review of the Research Landscape

πŸ“˜
Journal: INFORMATION
πŸ—“
Publish year: 2022

πŸ“ŽStudy paper

πŸ“±Channel: @ComplexNetworkAnalysis
#paper #Knowledge_Graphs #Research #Landscape #review
πŸ“„Knowledge Graph Completion: A Bird’s Eye View on Knowledge Graph Embeddings, Software Libraries, Applications and Challenges

πŸ—“Publish year: 2022

πŸ“ŽStudy paper

πŸ“±Channel: @ComplexNetworkAnalysis
#paper #Knowledge_Graphs #Embeddings #Software #Applications #Challenges
🎞 Machine Learning with Graphs: PageRank Random Walks and embedding

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

πŸ’₯In this lecture, -we will talk about an alternative approach, message passing. We will introduce the semi-supervised learning on predicting node labels by leveraging correlations that exist in the network. One key concept is the collective classification, which involves three steps including the local classifier that assigns initial labels, the relational classifier that captures correlations, and the collective inference that propagates correlations.
-we introduce belief propagation, which is a dynamic programming approach to answering probability queries in a graph. By iteratively passing messages to neighbors, the final belief is calculated if a consensus is reached. We then show the message passing with examples and generalization to tree structure. At last, we talk about the loopy belief propagation algorithm, and its pros and cons.
-we introduce the relational classifier and iterative classification for node classification. Starting from the relational classifier, we show how to iteratively update probabilities of node labels based on the labels of neighbors. We then talk about the iterative classification that improves the collective classification by predicting node label based on labels of neighbors as well as its features

πŸ“½ Watch: part1 part2 part3

πŸ“²Channel: @ComplexNetworkAnalysis

#video #course #Graph #Machine_Learning
πŸ“„Taxonomy of Link Prediction for Social Network Analysis: A Review

πŸ“˜
Journal: IEEE Access (I.F=3.476)
πŸ—“
Publish year: 2020

πŸ“ŽStudy paper

πŸ“±Channel: @ComplexNetworkAnalysis
#paper #Taxonomy #Link_Prediction #review
πŸ“„Knowledge graph and knowledge reasoning: A systematic review

πŸ“˜
Journal: Journal of Electronic Science and Technology
πŸ—“
Publish year: 2022

πŸ“ŽStudy paper

πŸ“±Channel: @ComplexNetworkAnalysis
#paper #Knowledge_graph #review
Knowledge_Graph_Embedding_A_Survey_of_Approaches_and_Applications.pdf
970.4 KB
πŸ“„Knowledge Graph Embedding: A Survey of Approaches and Applications

πŸ“˜Journal: IEEE Transactions on Knowledge and Data Engineering(I.F=6.997)

πŸ—“Publish year: 2017

πŸ“ŽStudy paper

πŸ“²Channel: @ComplexNetworkAnalysis
#paper
πŸ“„Gamification in education: A citation network analysis using
CitNetExplorer

πŸ“˜Journal: Contemporary Educational Technology(I.F=3.68)

πŸ—“Publish year: 2023

πŸ“ŽStudy paper

πŸ“²Channel: @ComplexNetworkAnalysis
#paper #CitNetExplorer