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🎞 Webinar: Social Network Analysis: Fundamental Concepts

πŸ’₯Free recorded Webinar

πŸ’₯This free webinar, organised by the UK Data Service, is the first in a series of three on understanding and using SNA methods for social science research purposes. In this webinar they cover the fundamental concepts and terms underpinning SNA, and demonstrate how network data is structured and differs from more traditional social science datasets (e.g. social surveys). We will also outline a simple analysis of social network data using the Python programming language. As a result of attending this webinar, participants will possess the necessary knowledge and vocabulary to undertake a SNA research project.

πŸ“½ Watch

πŸ“²Channel: @ComplexNetworkAnalysis

#video #Webinar #Social_Network
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πŸ“„Multi-Agent Systems and Complex Networks: Review and Applications in Systems Engineering

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Journal: PROCESSES(I.F=3.352)
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Publish year: 2020

πŸ“ŽStudy paper

πŸ“±Channel: @ComplexNetworkAnalysis
#paper #Multi_Agent #Applications #Systems #Engineering #Review
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πŸ“„A Review of Knowledge Graph Completion

πŸ“˜Journal: Information (I.F=3.38)
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publish year: 2022

πŸ“Ž Study the paper

πŸ“²Channel: @ComplexNetworkAnalysis
#paper #Review #Knowledge_Graph
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Credit_risk_and_financial_integration_An_application_of_network.pdf
835 KB
πŸ“„Credit risk and financial integration: An application of network analysis

πŸ“˜Journal: International Review of Financial Analysis (I.F=8.235)
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publish year: 2020

πŸ“Ž Study the paper

πŸ“²Channel: @ComplexNetworkAnalysis
#paper #financial #trade #weighted_network
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πŸ“„Graph Anomaly Detection with Graph Neural Networks: Current Status and Challenges

πŸ“˜
Journal: IEEE ACCESS (I.F=3.476)
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Publish year: 2022

πŸ“ŽStudy paper

πŸ“±Channel: @ComplexNetworkAnalysis
#paper #Anomaly #Graph_Neural_Networks #Status #Challenges
πŸ“„Blockchain Data Analysis from the Perspective of Complex Networks: Overview

πŸ“˜
Journal: Tsinghua Science and Technology (I.F=3.515)
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Publish year: 2022

πŸ“ŽStudy paper

πŸ“±Channel: @ComplexNetworkAnalysis
#paper #Blockchain #Perspective #Overview
πŸ“„A Survey of Graph Prompting Methods: Techniques, Applications, and Challenges

πŸ—“Publish year: 2023

πŸ“ŽStudy paper

πŸ“±Channel: @ComplexNetworkAnalysis
#paper #Graph #Prompting #Techniques #Applications #Challenges #Survey
πŸ“„From social networks to knowledge graphs: A plea for interdisciplinary approaches

πŸ“˜
Journal: Social Sciences and Humanities Open
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Publish year: 2022

πŸ“ŽStudy paper

πŸ“±Channel: @ComplexNetworkAnalysis
#paper #knowledge_graph #plea #interdisciplinary #approaches
πŸ“„Complex networks analysis: centrality measures

πŸ“˜Journal: Indonesian Journal of Electrical Engineering and Computer Science (I.F=1.51)
πŸ—“ publish year: 2023

πŸ“Ž Study the paper

πŸ“²Channel: @ComplexNetworkAnalysis
#paper #centrality
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πŸ“„A Survey on Knowledge Graph Embeddings for Link Prediction

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Journal: SYMMETRY-BASEL (I.F=2.94)
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Publish year: 2021

πŸ“ŽStudy paper

πŸ“±Channel: @ComplexNetworkAnalysis
#paper #knowledge_graph #Embeddings #Link_Prediction #Survey
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πŸ“‘ Protein interaction networks: centrality, modularity, dynamics, and applications

πŸ“˜
Journal: Frontiers of Computer Science (I.F.=2.669)
πŸ—“Publish year: 2021

πŸ“Ž Study the paper

πŸ“²Channel: @ComplexNetworkAnalysis
#review #ppi
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πŸ“„Graph (Network - Nodes and edges)

πŸ’₯Technical paper

πŸ’₯ In this paper, the auther will cover: Graph (Network - Nodes and edges), About, Articles Related, Application, Type, Structure, Example, Map, Directed Graph, Dominating set, Grow Algorithm, Shrink Algorithm, Path, Definition, Cycle, Spanning, Forest, Analysis, Documentation / Reference

🌐 Study

πŸ“²Channel: @ComplexNetworkAnalysis

#paper #Graph #python #code
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πŸ“„Introduction and Graph Structure

πŸ’₯Technical paper

πŸ’₯ In this paper, the auther begin by motivating the study of graph representations of data, or networks. Networks form a general language for desribing complex systems of interacting entities. Pictorially, rather than thinking that our dataset consists of a set of isolated data points, we consider interactions and relationships between these points.

🌐 Study

πŸ“²Channel: @ComplexNetworkAnalysis

#paper #Graph
πŸ“‘ A Review of Relational Machine Learning for Knowledge Graphs

πŸ“˜
Journal: Proceedings of the IEEE (I.F.=14.91)
πŸ—“Publish year: 2016

πŸ“Ž Study the paper

πŸ“²Channel: @ComplexNetworkAnalysis
#paper #review #Machine_Learning #Knowledge_Graphs
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πŸ“„A Graph Theory Based Systematic Literature Network Analysis

πŸ“˜
Journal: Theoretical Economics Letters
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Publish year: 2018

πŸ“ŽStudy paper

πŸ“±Channel: @ComplexNetworkAnalysis
#paper #Graph_Theory #Systematic #Literature