Network Analysis Resources & Updates
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📄Graph Learning: A Survey
📘Journal: IEEE Transactions on Artificial Intelligence
🗓Publish year: 2021
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #Graph #Survey
📄Survey of Attack Graph Analysis Methods from the Perspective of Data and Knowledge Processing
📘Journal: Security and communication networks (IF= 1.288)
🗓Publish year: 2019
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #Graph #Survey
📕Social Network Analysis
📝Authors: Stéphane Tufféry
💥Social networks are at the heart of big data, with their huge quantities of data of all kinds, text, images, video, and audio. Graphs are used to represent social networks in particular and all networks in general. In many applications of social networks, it is important to identify the most influential individuals. In a graph, the importance of a vertex can be expressed in several ways, the main ones being the degree centrality, the closeness centrality, the betweenness centrality, and prestige. A clique is a graph in which all vertices are connected and a quasi-clique is a group of vertices that are highly connected. A community is a subgraph that is both a quasi-clique and a quasi-connected component.
🗓 publish year: 2022
📖 Study book
📲Channel: @ComplexNetworkAnalysis
#book #R #code
📄Blockchain Network Analysis: A Comparative Study of Decentralized Banks?
🗓Publish year: 2022
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #Blockchain #Banks #review
📄Using Theory to Guide Exploratory Network Analyses
📘Journal: Faculty & Staff Research and Creative Activity
🗓Publish year: 2022
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #Graph
📄Social network analysis of open source software: A review and categorisation
📘Journal: INFORMATION AND SOFTWARE TECHNOLOGY (I.F=3.862)
🗓Publish year: 2021
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #software #categorisation #review
🎞 Financial Network Analysis using Python | Kalyan Prasad | Conf42 Python 2022
💥Free recorded workshop by Kalyan Prasad Data Scientist & Analytics Manager at Creative Crewz.
💥Historically, networks have been studied extensively in graph theory, an area of mathematics. After many applications to several different subjects including physics, health science, and sociology, over the last years, network analysis has become an active topic not only in data science but also in finance. In a nutshell, a network is a system with nodes connected by linkages.
Network analysis is popular to describe the characteristics or behaviors of complex networks. There has been also some research conducted to model the stock market using networks. The motivation is that the performances of certain stocks are often correlated, either because of the general market direction or the cyclicity of the same segments of the market.
📝In this talk, they are going to cover the following points:
• Introduction to Networks
• History & why graphs
• Finance evolution in networks
• Understanding Network structure
• Leveraging the power of Python Graphs
• Real-time finance usage of network analysis using two examples(hands-on)
• Wrap-up
📽 Watch
📲Channel: @ComplexNetworkAnalysis
#video #workshop #Graph #Python
📕Introduction to R for Data Science: A LISA 2020 Guidebook
📝Authors: Jacob D. Holster
💥This guidebook aims to provide readers an opportunity to make a start towards learning R for a variety of data science tasks, include (a) data cleaning and preparation, (b) statistical analysis, (c) data visualization, (d) natural language processing, (e) network analysis, and (f) Structural Equation Modeling to name a few. In Chapters 1 and 2 we invite readers to install R and RStudio and to start manipulating data for analysis. Chapter 3 and Chapter 4 include introductory exercises to teach data visualization and statistical analysis in R. In Chapter 5 and beyond, you will explore basic analytic concepts (e.g., correlation and regression) and more advanced approaches to data modeling through the lenses of Structural Equation Modeling, Network Analysis, and Text Analysis.
📚Free online guidebook
📖 Study
💻 Code
📲Channel: @ComplexNetworkAnalysis
#book #R #code #video
🎞 Think Graph Neural Networks (GNN) are hard to understand? Try this two part series..
💥Free recorded tutorial by Avkash Chauhan.
💥This tutorial is part one of a two parts GNN series. Graphs helps us understand and visualize the relationship and connection information in a natural and close to human behavior. Graph Neural networks are solving various machine learning problems where CNN or convolutional neural networks can not be applied. Then You will learn GNN technical details along with hands on exercise using Python programming along with NetworkX, PyG (pytorch_geometric) , matplotlib libraries.
📽 Watch: part1 part2
💻 Code
📜 Slides
📲Channel: @ComplexNetworkAnalysis
#video #tutorial #Graph #GNN #Python #NetworkX #PyG
📣 Graph Structure and Complex Network Analysis
💥INTERNATIONAL CENTER FOR PURE AND ACCURATE MATHEMATICS
💥Understanding their graph structure is a key point in deriving efficient algorithms in large networks. In this school, we will cover theoretical aspects of graph structure analysis as well as applications on complex network studies with 9 lectures in two main axes:
1) Exploiting graph structure to efficiently solve combinatorial problems
2) Extending graph structural analysis to complex network studies
📌 SIRINCE , Turkey
💬 Language: English
🗓 04/06/2023 to 16/06/2023
🕖 Deadline : February 21, 2023
👨🏫 Scientific committee:
Tınaz Eki̇m, Bertrand Jouve, Pascale KUNTZ, Saieed Akbari, Pınar Heggernes, Marc Demange
📎Link
ℹ️ Register + more information
📲Channel: @ComplexNetworkAnalysis
#CIMPA_schools
📄Implementation and Understanding of Graph Neural Networks(GNN)
💥Technical paper
🌐 Study
📲Channel: @ComplexNetworkAnalysis
#paper #GNN #code #PyTorch
🎞 Conducting Network Analysis in R
💥Free recorded webinar
🔹This webinar, which is sponsored by the AED Early Career Special Interest Group (SIG), will provide guidance on how network analysis is a statistical approach that allows for the examination of how components of a network are related to one another.In this webinar, Dr. Cheri Levinson and her advanced graduate student Ms. Irina Vanzhula will provide a brief overview on network theory and analysis. They will then demonstrate how to conduct network analysis in R using sample data.
📽 Watch
📱Channel: @ComplexNetworkAnalysis
#video #R
📄Complex Networks: Erdős–Rényi Model, Centralities, Random Regular Graph
💥Complex Networks are traditionally studied in the context of Graph theory, and identify important nodes and edges with the notions of centrality.
💥free online site to visualize, test and see different metrics in complex network.
📎 Link
📲Channel: @ComplexNetworkAnalysis
#paper #Centralities
📄Application of Association Rule Mining and Social Network Analysis for Understanding Causality of Construction Defects
📘Journal: SUSTAINABILITY(I.F=3.889)
🗓Publish year: 2019
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #Application #Causality #Defects
📄A Review of Complex Systems Approaches to Cancer Networks
📘Journal: Complex Systems
🗓Publish year: 2020
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #cancer #review
🎞 Machine Learning with Graphs: Traditional Feature-based Methods
💥Free recorded course by Jure Leskovec, Computer Science, PhD
💥In this lecture they focus on how to represent graphs as matrices and discuss subsequent properties that can explore. then define the notion of PageRank, further explore Random Walks, and introduce Matrix Factorization as a perspective for generating node embeddings.
📽 Watch: part1 part2 part3 part4
📜 Slides
📲Channel: @ComplexNetworkAnalysis
#video #course #Graph #Machine_Learning
🎞 Eric Ma: Network Analysis Made Simple
💥Free recorded tutorial
🔹Have you ever wondered about how data scientists at Facebook and LinkedIn make friend recommendations? Or how epidemiologists track down patient zero in an outbreak? If so, then this tutorial is for you. In this tutorial, will use a variety of datasets to help you understand the fundamentals of network thinking, with a particular focus on constructing, summarizing, visualizing, and using complex networks to solve problems
📽 Watch
📱Channel: @ComplexNetworkAnalysis
#video
📄Graph Theoretical Analysis of Brain Network Characteristics in Brain Tumor Patients: A Systematic Review
📘Journal: Neuropsychology Review (I.F= 6.75)
🗓Publish year: 2021
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #Brain #Review
📄Basics on network theory to analyze biological systems: a hands-on outlook
📘Journal: Functional & Integrative Genomics (I.F= 3.41)
🗓Publish year: 2022
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #biological_network
+1📝Booklet: Structure and Dynamics of Information in Networks
💥David Kempe, Department of Computer Science, University of Southern California
🗓Publish year: 2021
📎Study Booklet
📱Channel: @ComplexNetworkAnalysis
#Booklet #Structure #Dynamics #Information
