Network Analysis Resources & Updates – Telegram
Network Analysis Resources & Updates
3.08K subscribers
861 photos
163 files
1.16K 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
📕 The Structure and Dynamics of Networks

🌐 Download the ebook

📲Channel: @ComplexNetworkAnalysis

#ebook
📄Centralities in complex networks

🗓Publish year: 2019

📎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
📄Dynamic Development Analysis of Complex Network Research: A Bibliometric Analysis

📘Journal: Complexity (I.F= 2,83 )
🗓Publish year: 2022

📎Study paper

📲Channel: @ComplexNetworkAnalysis
#paper
2021_Application_of_complex_systems_topologies_in_artificial_neural.pdf
860.1 KB
📄Application of complex systems topologies in artificial neural networks optimization: An overview

📘Journal: Expert Systems with Applications (I.F= 6.954)
🗓Publish year: 2021

📎Study paper

📲Channel: @ComplexNetworkAnalysis
#paper #biology #link_prediction
👍1
📕 Social Network Data Analytics

🌐 Download the ebook

📲Channel: @ComplexNetworkAnalysis

#ebook
👍1
📄Random complex networks

📘Journal
: National Science Review(I.F= 16.693)

📎Study paper

📲Channel: @ComplexNetworkAnalysis
#paper
🎞 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
2018_Link prediction potentials for biological networks.pdf
407.2 KB
📄 Link prediction potentials for biological networks

📘 Journal: International Journal of Data Mining and Bioinformatics (I.F=0.667)

🗓 Publish year: 2018

📎 Study paper

📱Channel:
@ComplexNetworkAnalysis
#paper #linkprediction #biology
📕 Network Analysis: Methodological Foundations

🌐 Download the ebook

📲Channel: @ComplexNetworkAnalysis

#ebook
🎞 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
📄A Survey of Link Prediction in Complex Networks

🗓Publish year: 2016

📎Study paper

📲Channel: @ComplexNetworkAnalysis
#paper #Survey #linkprediction
📄Complex Networks in Manufacturing and Logistics: A Retrospect

📘 Book: Dynamics in Logistics

🗓Publish year: 2021

📎Study paper

📲Channel: @ComplexNetworkAnalysis
#paper
📄A complex network approach to time series analysis with application in diagnosis of neuromuscular disorders

🗓Publish year: 2021

📎Study paper

📲Channel: @ComplexNetworkAnalysis
#paper
👍1
Forwarded from Bioinformatics
🎬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
📄 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 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
📄 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
👍4
🎞 Random graphs

💥Free recorded Lecture by Prof. Leonid Zhukov, Ilya Makarov.

💥Erdos-Reni random graph model. Poisson and Bernulli distributions. Distribution of node degrees. Phase transition, gigantic connected component. Diameter and cluster coefficient. Configuration model
.

📽 Watch

📑 Lecture

📲Channel: @ComplexNetworkAnalysis

#video #Lecture
Complex Networks in Software, Knowledge, and Social Systems
👇👇👇👇👇