🎞 Introduction to Social Network Analysis [3/5]: Historical Applications
💥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
💥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
YouTube
Introduction to Social Network Analysis [3/5]: Historical Applications
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.
The script is available here: https://doi.org/10.5281/zenodo.5083036…
The script is available here: https://doi.org/10.5281/zenodo.5083036…
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2020_Review_on_Social_Network_Trust_With_Respect_To_Big_Data_Analytics.pdf
328.4 KB
📄Review on Social Network Trust With Respect To Big Data Analytics
📘Conference: Fourth International Conference on Trends in Electronics and Informatics (ICOEI 2020)
🗓Publish year: 2020
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #review
📘Conference: Fourth International Conference on Trends in Electronics and Informatics (ICOEI 2020)
🗓Publish year: 2020
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #review
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🎞 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
💥This free recorded tutorial goes from import through the whole analysis phase for a citation network.
📽 Watch
📱Channel: @ComplexNetworkAnalysis
#video #tutorial #gephi
YouTube
Gephi Tutorial on Network Visualization and Analysis
This tutorial goes from import through the whole analysis phase for a citation network. Data can be accessed at http://www.cs.umd.edu/~golbeck/INST633o/Viz.shtml
📄Centralities in complex networks
🗓Publish year: 2019
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper
🗓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
💥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
YouTube
Emergence of echo chambers and polarization dynamics in social networks - Michele Starnini
Emergence of echo chambers and polarization dynamics in social networks
Abstract: Echo chambers and opinion polarization, recently quantified in several sociopolitical contexts and across different social media, raise concerns on their potential impact on…
Abstract: Echo chambers and opinion polarization, recently quantified in several sociopolitical contexts and across different social media, raise concerns on their potential impact on…
📄Dynamic Development Analysis of Complex Network Research: A Bibliometric Analysis
📘Journal: Complexity (I.F= 2,83 )
🗓Publish year: 2022
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper
📘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
📘Journal: Expert Systems with Applications (I.F= 6.954)
🗓Publish year: 2021
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #biology #link_prediction
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📄Random complex networks
📘Journal: National Science Review(I.F= 16.693)
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper
📘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
💥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
YouTube
Order and Disorder in Network Science - Renaud Lambiotte
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…
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
📘 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
🌐 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
💥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
YouTube
Lecture 2. Power law and scale-free networks.
Network Science 2021 @ HSE
http://www.leonidzhukov.net/hse/2021/networks/
http://www.leonidzhukov.net/hse/2021/networks/
📄A Survey of Link Prediction in Complex Networks
🗓Publish year: 2016
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #Survey #linkprediction
🗓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
📘 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
🗓Publish year: 2021
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper
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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
👩🏫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