🎞 Course "Social Network Analysis". Lecture 1. Terminology
💥Free recorded course by Leonid Zhukov
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📱Channel: @ComplexNetworkAnalysis
#video #Terminology
💥Free recorded course by Leonid Zhukov
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📱Channel: @ComplexNetworkAnalysis
#video #Terminology
YouTube
Course "Social Network Analysis" (Leonid Zhukov). Lecture 1. Terminology
Course outline:
- Introduction to network science
- Descriptive network analysis
- Mathematical models of networks
- Node centrality and ranking on networks
- Network communities
- Network structure and visualization
- Social media and information flow in…
- Introduction to network science
- Descriptive network analysis
- Mathematical models of networks
- Node centrality and ranking on networks
- Network communities
- Network structure and visualization
- Social media and information flow in…
2016-Machine Learning in Complex Networks (1).pdf
8.5 MB
📘 Machine Learning in Complex Networks
📝Authors: Thiago Christiano Silva, Liang Zhao
📅Publish year: 2016
💥This book presents the features and advantages offered by complex networks in the machine learning domain. In the first part, an overview on complex networks and network-based machine learning is presented, offering necessary background material. In the second part, we describe in details some specific techniques based on complex networks for supervised, non-supervised, and semi-supervised learning. Particularly, a stochastic particle competition technique for both non-supervised and semi-supervised learning using a stochastic nonlinear dynamical system is described in details. Moreover, an analytical analysis is supplied, which enables one to predict the behavior of the proposed technique. In addition, data reliability issues are explored in semi-supervised learning.
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📲Channel: @ComplexNetworkAnalysis
#book #Machine_Learning
📝Authors: Thiago Christiano Silva, Liang Zhao
📅Publish year: 2016
💥This book presents the features and advantages offered by complex networks in the machine learning domain. In the first part, an overview on complex networks and network-based machine learning is presented, offering necessary background material. In the second part, we describe in details some specific techniques based on complex networks for supervised, non-supervised, and semi-supervised learning. Particularly, a stochastic particle competition technique for both non-supervised and semi-supervised learning using a stochastic nonlinear dynamical system is described in details. Moreover, an analytical analysis is supplied, which enables one to predict the behavior of the proposed technique. In addition, data reliability issues are explored in semi-supervised learning.
📎 Study the book
📲Channel: @ComplexNetworkAnalysis
#book #Machine_Learning
👍3
📄A survey on text mining in social networks
📘Journal: KNOWLEDGE ENGINEERING REVIEW (I.F= 2.016)
🗓Publish year: 2015
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #text_mining #survey
📘Journal: KNOWLEDGE ENGINEERING REVIEW (I.F= 2.016)
🗓Publish year: 2015
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #text_mining #survey
📄Challenges and Limitations of Biological Network Analysis
📘Journal: BioTech
🗓Publish year: 2022
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #Biological
📘Journal: BioTech
🗓Publish year: 2022
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #Biological
👍4
📄A survey on hierarchical community detection in large-scale complex networks
📘Journal: AUT Journal of Mathematics and Computing
🗓Publish year: 2022
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #community #large_scale #survey
📘Journal: AUT Journal of Mathematics and Computing
🗓Publish year: 2022
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #community #large_scale #survey
🎞 Machine Learning with Graphs
💥Free recorded course by Jure Leskovec, Computer Science, PhD
💥Graphs are a general language for describing and analyzing entities with relations/interactions. There are many types of networks and graphs, such as social networks, communication and transaction networks, biomedine networks, brain networks, etc. In this course, we will take advantage of relational structure for better prediction.
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📜 Slides
📲Channel: @ComplexNetworkAnalysis
#video #course #Graph #Machine_Learning
💥Free recorded course by Jure Leskovec, Computer Science, PhD
💥Graphs are a general language for describing and analyzing entities with relations/interactions. There are many types of networks and graphs, such as social networks, communication and transaction networks, biomedine networks, brain networks, etc. In this course, we will take advantage of relational structure for better prediction.
📽 Watch
📜 Slides
📲Channel: @ComplexNetworkAnalysis
#video #course #Graph #Machine_Learning
👍2
📄Consensus clustering in complex networks
📘Journal: Scientific Reports(I.F=5.516)
🗓Publish year: 2012
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #Consensus_clustering
📘Journal: Scientific Reports(I.F=5.516)
🗓Publish year: 2012
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #Consensus_clustering
👍1
📄Network analysis approach to Likert-style surveys
📘Journal: PHYSICAL REVIEW PHYSICS EDUCATION RESEARCH (I.F=2.359)
🗓Publish year: 2022
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #Likert_style #survey
📘Journal: PHYSICAL REVIEW PHYSICS EDUCATION RESEARCH (I.F=2.359)
🗓Publish year: 2022
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #Likert_style #survey
📄Motif discovery algorithms in static and temporal networks: A survey
📘Journal: Journal of Complex Networks(I.F=2.011)
🗓Publish year: 2020
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #Motif #survey
📘Journal: Journal of Complex Networks(I.F=2.011)
🗓Publish year: 2020
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #Motif #survey
👍2
🎞 Closeness Centrality & Betweenness Centrality: A Social Network Lab in R for Beginners
💥Free recorded course
💥So what then is “closeness” or “betweenness” in a network? How do we figure these things out and how do we interpret them? This video is part of a series where we give you the basic concepts and options, and we walk you through a Lab where you can experiment with designing a network on your own in R. Hosted by Jonathan Morgan and the Duke University Network Analysis Center.
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📲Channel: @ComplexNetworkAnalysis
#video #course #Closeness_Centrality #Betweenness_Centrality #code #R
💥Free recorded course
💥So what then is “closeness” or “betweenness” in a network? How do we figure these things out and how do we interpret them? This video is part of a series where we give you the basic concepts and options, and we walk you through a Lab where you can experiment with designing a network on your own in R. Hosted by Jonathan Morgan and the Duke University Network Analysis Center.
📽 Watch
📲Channel: @ComplexNetworkAnalysis
#video #course #Closeness_Centrality #Betweenness_Centrality #code #R
YouTube
Closeness Centrality & Betweenness Centrality: A Social Network Lab in R for Beginners
DOWNLOAD Lab Code & Cheat Sheet: https://drive.google.com/open?id=0B2JdxuzlHg7OYnVXS2xNRWZRODQ
So what then is “closeness” or “betweenness” in a network? How do we figure these things out and how do we interpret them? This video is part of a series where…
So what then is “closeness” or “betweenness” in a network? How do we figure these things out and how do we interpret them? This video is part of a series where…
📄Analysis of Network Clustering Algorithms and Cluster Quality Metrics at Scale
📘Journal: PLOS ONE(I.F=3.752)
🗓Publish year: 2016
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #Clustering
📘Journal: PLOS ONE(I.F=3.752)
🗓Publish year: 2016
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #Clustering
📄A survey of game theory as applied to social networks
📘Journal: T singhua Science and Technology (I.F=3.515)
🗓Publish year: 2020
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #game_theory #survey
📘Journal: T singhua Science and Technology (I.F=3.515)
🗓Publish year: 2020
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #game_theory #survey
👍1
🎞 Network Analysis in Systems Biology
💥Free recorded course by Avi Ma’ayan, PhD
💥An introduction to data integration and statistical methods used in contemporary Systems Biology, Bioinformatics and Systems Pharmacology research. The course covers methods to process raw data from genome-wide mRNA expression studies (microarrays and RNA-seq) including data normalization, differential expression, clustering, enrichment analysis and network construction. The course contains practical tutorials for using tools and setting up pipelines, but it also covers the mathematics behind the methods applied within the tools. The course is mostly appropriate for beginning graduate students and advanced undergraduates majoring in fields such as biology, math, physics, chemistry, computer science, biomedical and electrical engineering. The course should be useful for researchers who encounter large datasets in their own research. The course presents software tools developed by the Ma’ayan Laboratory
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📲Channel: @ComplexNetworkAnalysis
#video #course #Biology
💥Free recorded course by Avi Ma’ayan, PhD
💥An introduction to data integration and statistical methods used in contemporary Systems Biology, Bioinformatics and Systems Pharmacology research. The course covers methods to process raw data from genome-wide mRNA expression studies (microarrays and RNA-seq) including data normalization, differential expression, clustering, enrichment analysis and network construction. The course contains practical tutorials for using tools and setting up pipelines, but it also covers the mathematics behind the methods applied within the tools. The course is mostly appropriate for beginning graduate students and advanced undergraduates majoring in fields such as biology, math, physics, chemistry, computer science, biomedical and electrical engineering. The course should be useful for researchers who encounter large datasets in their own research. The course presents software tools developed by the Ma’ayan Laboratory
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📲Channel: @ComplexNetworkAnalysis
#video #course #Biology
Coursera
Network Analysis in Systems Biology
Offered by Icahn School of Medicine at Mount Sinai. This ... Enroll for free.
📄Social Network Analysis and Spectral Clustering in Graphs and Networks
💥Technical paper
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📲Channel: @ComplexNetworkAnalysis
#paper #Spectral_Clustering #Graph #Code #Python
💥Technical paper
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📲Channel: @ComplexNetworkAnalysis
#paper #Spectral_Clustering #Graph #Code #Python
Medium
Social Network Analysis and Spectral Clustering in Graphs and Networks
Introduction to centrality measures and partitioning techniques in graphs
🎞 Consul and Complex Networks
💥Free recorded course by James Phillips, Consul Lead at HashiCorp
💥A systematic overview of Consul's different network models, how they work, what kind of use cases they serve, and how prepared queries can help provide glue to keep service discovery simple across all.
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📲Channel: @ComplexNetworkAnalysis
#video #course #Consul
💥Free recorded course by James Phillips, Consul Lead at HashiCorp
💥A systematic overview of Consul's different network models, how they work, what kind of use cases they serve, and how prepared queries can help provide glue to keep service discovery simple across all.
📽 Watch
📲Channel: @ComplexNetworkAnalysis
#video #course #Consul
YouTube
Consul and Complex Networks
James Phillips, Consul Lead at HashiCorp
A systematic overview of Consul's different network models, how they work, what kind of use cases they serve, and how prepared queries can help provide glue to keep service discovery simple across all.
For information…
A systematic overview of Consul's different network models, how they work, what kind of use cases they serve, and how prepared queries can help provide glue to keep service discovery simple across all.
For information…
👍2
📄Network-based machine learning and graph theory algorithms for precision oncology
📘Journal: npj Precision Oncology(I.F=10.092)
🗓Publish year: 2017
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #machine_Learning #graph
📘Journal: npj Precision Oncology(I.F=10.092)
🗓Publish year: 2017
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #machine_Learning #graph
📄INTRODUCTION TO COMPLEX NETWORK ANALYSIS
💥Technical paper
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📲Channel: @ComplexNetworkAnalysis
#paper
💥Technical paper
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#paper
Medium
INTRODUCTION TO COMPLEX NETWORK ANALYSIS
Complex Network Analysis studies how to recognise, describe, visualise and analyse complex networks. The most prominent way of analysing…
👍6
📄Cliques, Clusters and Components
💥Technical paper
💥Social Network Analysis for Startups by Maksim Tsvetovat, Alexander
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📲Channel: @ComplexNetworkAnalysis
#paper #Clustering #Graph #Code #Python
💥Technical paper
💥Social Network Analysis for Startups by Maksim Tsvetovat, Alexander
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📲Channel: @ComplexNetworkAnalysis
#paper #Clustering #Graph #Code #Python
O’Reilly Online Learning
Social Network Analysis for Startups
Chapter 4. Cliques, Clusters and Components In the previous chapter, we mainly talked about properties of individuals in a social network. In this chapter, we start working with progressively larger … - Selection from Social Network Analysis for Startups…
📄Complex Network: Facebook friends list
💥Technical paper
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📲Channel: @ComplexNetworkAnalysis
#paper
💥Technical paper
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📲Channel: @ComplexNetworkAnalysis
#paper
Medium
Complex Network: Facebook friends list
A small introduction to complex network analysis and the tools used.
🎞 clustering and motifs
💥Free recorded course
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📲Channel: @ComplexNetworkAnalysis
#video #course #clustering #motif
💥Free recorded course
📽 Watch
📲Channel: @ComplexNetworkAnalysis
#video #course #clustering #motif
YouTube
Social Network Analysis || 02 5B clustering and motifs 20 45
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📄Complex network approaches to nonlinear time series analysis
📘Journal: Physics Reports (I.F=25.6)
🗓Publish year: 2019
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #time_series
📘Journal: Physics Reports (I.F=25.6)
🗓Publish year: 2019
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #time_series