Network Analysis Resources & Updates

📄 Network analysis of protein interaction data 💥Free course From EMBL-EBI 💥This course provides an introduction to the theory and concepts of network analysis. It explores some of the features of protein-protein interaction networks and their implications for biology. Finally, the course discusses the tools and strategies that can be used to build and analyse biological networks. 📎Study course 📲Channel: @ComplexNetworkAnalysis #course

🎞 Introduction to Social Network Analysis [4/5]: Graph Interpretation 💥Free recorded workshop by Martin Grandjean (Université de Lausanne) at the Conference HNR+ResHist2021 Conference "Historical Networks - Réseaux Historiques - Historische Netzwerke co-organised by HNR and ResHist. 📽 Watch 📲Channel: @ComplexNetworkAnalysis #video #workshop

📄 Seven-Layer Model in Complex Networks Link Prediction: A Survey 📘Journal: Sensors (I.F=3.576) 🗓Publish year: 2020 📎 Study paper 📱Channel: @ComplexNetworkAnalysis #paper #survey #linkprediction

🎬Introduction to Biological Network Analysis 👩‍🏫Mini Courses from Donna Slonim at Tufts University Session 1: Network Basics and Properties Session 2: From Graphs to Function Session 3: Identifying Network Modules Session 4: Network Alignment and Querying 📲Channel: @Bioinformatics

📄A complex network approach to time series analysis with application in diagnosis of neuromuscular disorders 🗓Publish year: 2021 📎Study paper 📲Channel: @ComplexNetworkAnalysis #paper

📄Complex Networks in Manufacturing and Logistics: A Retrospect 📘 Book: Dynamics in Logistics 🗓Publish year: 2021 📎Study paper 📲Channel: @ComplexNetworkAnalysis #paper

📄A Survey of Link Prediction in Complex Networks 🗓Publish year: 2016 📎Study paper 📲Channel: @ComplexNetworkAnalysis #paper #Survey #linkprediction

🎞 Power law and scale-free networks. 💥Free recorded Lecture by Prof. Leonid Zhukov, Ilya Makarov. 💥Power law distribution. Scale-free networks.Pareto distribution, normalization, moments. Zipf law. Rank-frequency plot. 📽 Watch 📑Lecture 📲Channel: @ComplexNetworkAnalysis #video #Lecture

📕 Network Analysis: Methodological Foundations 🌐 Download the ebook 📲Channel: @ComplexNetworkAnalysis #ebook

🎞 Order and Disorder in Network Science 💥A recurring theme in the study of complex systems is the emergence of order and disorder in systems. Historically, one can think of the Boltzmann equation, and the irreversible growth of disorder at the macroscopic scale from reversible dynamics at the microscopic scale. Reversely, scientists have been fascinated by the emergence of spatial and temporal patterns in interacting systems. In this talk, I will give a personal view on these two sides within the field of network science, whose combination of order and randomness is at the core of several works on network dynamics and algorithms. 📽 Watch 📱Channel: @ComplexNetworkAnalysis #video #tutorial

📄Random complex networks 📘Journal: National Science Review(I.F= 16.693) 📎Study paper 📲Channel: @ComplexNetworkAnalysis #paper

📕 Social Network Data Analytics 🌐 Download the ebook 📲Channel: @ComplexNetworkAnalysis #ebook

📄Dynamic Development Analysis of Complex Network Research: A Bibliometric Analysis 📘Journal: Complexity (I.F= 2,83 ) 🗓Publish year: 2022 📎Study paper 📲Channel: @ComplexNetworkAnalysis #paper

🎞 Emergence of echo chambers and polarization dynamics in social networks 💥Echo chambers and opinion polarization, recently quantified in several sociopolitical contexts and across different social media, raise concerns on their potential impact on the spread of misinformation and on the openness of debates. Despite increasing efforts, the dynamics leading to the emergence of these phenomena stay unclear. In this talk, we will first review empirical evidence for the presence of echo chambers across social media platforms, by performing a comparative analysis among Gab, Facebook, Reddit, and Twitter. Then, we will present a simple modeling framework able to reproduce the observed opinion segregation in the social network. We consider networked agents characterized by heterogeneous activities and homophily, whose opinions can be reinforced by interactions with like-minded peers. We show that the transition between a global consensus and emerging polarized states in the network can be analytically characterized as a function of the social influence of the agents and the controversialness of the topic discussed. Finally, we consider a generalization to multiple opinions with respect to different topics. Inspired by skew coordinate systems recently proposed in natural language processing models, we frame this problem in a formalism in which opinions evolve in a multidimensional space where topics form a non-orthogonal basis. We show that this approach can reproduce the correlations between extreme opinions on different topics found in survey data. 📽 Watch 📱Channel: @ComplexNetworkAnalysis #video #tutorial

📄Centralities in complex networks 🗓Publish year: 2019 📎Study paper 📲Channel: @ComplexNetworkAnalysis #paper

📕 The Structure and Dynamics of Networks 🌐 Download the ebook 📲Channel: @ComplexNetworkAnalysis #ebook

🎞 Gephi Tutorial on Network Visualization and Analysis 💥This free recorded tutorial goes from import through the whole analysis phase for a citation network. 📽 Watch 📱Channel: @ComplexNetworkAnalysis #video #tutorial #gephi