Understanding Ethereum via Graph Analysis.pdf
1.6 MB
📑 Understanding Ethereum via Graph Analysis
📘Conference: IEEE Conference on Computer Communications
🗓Publish year: 2018
📎 Study the paper
📲Channel: @ComplexNetworkAnalysis
#paper #Ethereum #Graph
📘Conference: IEEE Conference on Computer Communications
🗓Publish year: 2018
📎 Study the paper
📲Channel: @ComplexNetworkAnalysis
#paper #Ethereum #Graph
👍2
📄Representation Learning on Graphs: Methods and Applications
🗓Publish year: 2017
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #Representation_Learning #Methods #Applications
🗓Publish year: 2017
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #Representation_Learning #Methods #Applications
👍2🔥1
📄From past to present: Spam detection and identifying opinion leaders in social networks
📘Journal : SIGMA JOURNAL OF ENGINEERING AND NATURAL SCIENCES
🗓Publish year: 2022
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #past #present #Spam_detection #identifying #opinion #leaders
📘Journal : SIGMA JOURNAL OF ENGINEERING AND NATURAL SCIENCES
🗓Publish year: 2022
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #past #present #Spam_detection #identifying #opinion #leaders
👍3👏1
2022_A_Review_on_Opinion_Leader_Detection_and_its_Applications.pdf
630.7 KB
📄A Review on Opinion Leader Detection and its Applications
📘Conference: International Conference on Communication and Electronics Systems (ICCES)
🗓Publish year: 2022
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #Opinion #Leader #paper #Detection #Applications #Review
📘Conference: International Conference on Communication and Electronics Systems (ICCES)
🗓Publish year: 2022
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #Opinion #Leader #paper #Detection #Applications #Review
👍2
📄 20 years of network community detection
📘journal: NATURE PHYSICS(I.F=19.684)
🗓Publish year: 2022
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #years #community_detection
📘journal: NATURE PHYSICS(I.F=19.684)
🗓Publish year: 2022
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #years #community_detection
👍3
2023_A_survey_on_identification_of_influential_users_in_social_media.pdf
460.6 KB
📄 A survey on identification of influential users in social media networks using bio inspired algorithms
📘journal: Procedia Computer Science
🗓Publish year: 2023
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #identification #influential #users #bio #inspired #algorithms
📘journal: Procedia Computer Science
🗓Publish year: 2023
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #identification #influential #users #bio #inspired #algorithms
👍3
2017-Python for Graph and Network Analysis.pdf
13 MB
📕Python for Graph and Network Analysis
🗓Publish year: 2017
📎 Study the book
📱Channel: @ComplexNetworkAnalysis
#book #Python #Graph
🗓Publish year: 2017
📎 Study the book
📱Channel: @ComplexNetworkAnalysis
#book #Python #Graph
👏3
📑 Link Prediction on Complex Networks: An Experimental Survey
📘journal: Data Science and Engineering (I.F=4.52)
🗓Publish year: 2022
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📲Channel: @ComplexNetworkAnalysis
#paper #Link_Prediction #Survey
📘journal: Data Science and Engineering (I.F=4.52)
🗓Publish year: 2022
📎 Study the paper
📲Channel: @ComplexNetworkAnalysis
#paper #Link_Prediction #Survey
👍2
📑Graph-powered learning methods in the Internet of Things: A survey
📘journal: Machine Learning with Applications (I.F=3.203)
🗓Publish year: 2023
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📲Channel: @ComplexNetworkAnalysis
#paper #IOT #Survey
📘journal: Machine Learning with Applications (I.F=3.203)
🗓Publish year: 2023
📎 Study the paper
📲Channel: @ComplexNetworkAnalysis
#paper #IOT #Survey
👍3
From_Social_Networks_to_Time_Series_Methods_and_Applications_1.pdf
1 MB
📕From Social Networks to Time Series: Methods and Applications
📝Authors: Tongfeng Weng, Yaofeng Zhang, Pan Hui.
🗓 publish year: 2017
📖 Study book
📲Channel: @ComplexNetworkAnalysis
#book #Social_Network #Application
📝Authors: Tongfeng Weng, Yaofeng Zhang, Pan Hui.
🗓 publish year: 2017
📖 Study book
📲Channel: @ComplexNetworkAnalysis
#book #Social_Network #Application
👍4
🎞 Machine Learning with Graphs: Theory of Graph Neural Networks
💥Free recorded course by Jure Leskovec, Computer Science, PhD
💥The topics: How expensive are graph neural networks, designing the most powerful GNNs.
📽 Watch: part1 part2
📲Channel: @ComplexNetworkAnalysis
#video #course #Graph #Machine_Learning #GNN
💥Free recorded course by Jure Leskovec, Computer Science, PhD
💥The topics: How expensive are graph neural networks, designing the most powerful GNNs.
📽 Watch: part1 part2
📲Channel: @ComplexNetworkAnalysis
#video #course #Graph #Machine_Learning #GNN
YouTube
Stanford CS224W: ML with Graphs | 2021 | Lecture 9.1 - How Expressive are Graph Neural Networks
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3GwTmur
Jure Leskovec
Computer Science, PhD
In this lecture, we provide a theoretical framework to analyze the expressive power…
Jure Leskovec
Computer Science, PhD
In this lecture, we provide a theoretical framework to analyze the expressive power…
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📄 Precision medicine — networks to the rescue
📘journal: Current Opinion in Biotechnology (COBIOT) (I.F=10.279)
🗓Publish year: 2020
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #iPrecision #medicine #networks #rescue
📘journal: Current Opinion in Biotechnology (COBIOT) (I.F=10.279)
🗓Publish year: 2020
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #iPrecision #medicine #networks #rescue
👍4
📄 Role-Aware Information Spread in Online Social Networks
📘journal: ENTROPY-SWITZ (I.F=2.738)
🗓Publish year: 2021
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #Role_Aware #Information #Spread #Online
📘journal: ENTROPY-SWITZ (I.F=2.738)
🗓Publish year: 2021
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #Role_Aware #Information #Spread #Online
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📑A Review of Graph and Network Complexity from an Algorithmic Information Perspective
📘journal: Entropy (I.F=2.738)
🗓Publish year: 2018
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📲Channel: @ComplexNetworkAnalysis
#paper #Graph #Review
📘journal: Entropy (I.F=2.738)
🗓Publish year: 2018
📎 Study the paper
📲Channel: @ComplexNetworkAnalysis
#paper #Graph #Review
👍5👏1
📄 A survey of community detection methods in multilayer networks
📘journal: Data Mining and Knowledge Discovery (I.F=5.406)
🗓Publish year: 2021
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #community_detection #methods #multilayer #survey
📘journal: Data Mining and Knowledge Discovery (I.F=5.406)
🗓Publish year: 2021
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #community_detection #methods #multilayer #survey
👍1
📑Considering weights in real social networks: A review
📘journal: Frontiers in Physics(I.F=3.718)
🗓Publish year: 2023
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📲Channel: @ComplexNetworkAnalysis
#paper #social_networks #Review
📘journal: Frontiers in Physics(I.F=3.718)
🗓Publish year: 2023
📎 Study the paper
📲Channel: @ComplexNetworkAnalysis
#paper #social_networks #Review
👍2👏1
📄 Community detection for multilayer weighted networks
📘journal: Information Sciences(I.F=8.233)
🗓Publish year: 2022
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #Community_detection #multilayer #weighted_networks
📘journal: Information Sciences(I.F=8.233)
🗓Publish year: 2022
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #Community_detection #multilayer #weighted_networks
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📑Recent Advances in Graph-based Machine Learning for Applications in Smart Urban Transportation Systems
🗓Publish year: 2023
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📲Channel: @ComplexNetworkAnalysis
#paper #machine_learning #Application
🗓Publish year: 2023
📎 Study the paper
📲Channel: @ComplexNetworkAnalysis
#paper #machine_learning #Application
👍4
🎞 Network Analysis of Organizations
💥Free recorded course by professor Daniel A. McFarland.
💥In this course, we will describe how organization’s researchers look at social networks within organizations. In addition, we will describe how some theorists contend there is a network form of organization that is distinct from hierarchical organizations and markets. So we will relate two perspectives: a purely analytic one that describes networks within organizations, and a theoretical one concerning a prescribed form of inter- organizational association that can result in better outputs.
📽 Watch
📲Channel: @ComplexNetworkAnalysis
#video #course #network
💥Free recorded course by professor Daniel A. McFarland.
💥In this course, we will describe how organization’s researchers look at social networks within organizations. In addition, we will describe how some theorists contend there is a network form of organization that is distinct from hierarchical organizations and markets. So we will relate two perspectives: a purely analytic one that describes networks within organizations, and a theoretical one concerning a prescribed form of inter- organizational association that can result in better outputs.
📽 Watch
📲Channel: @ComplexNetworkAnalysis
#video #course #network
👏2
📄 Review on Learning and Extracting Graph Features for Link Prediction
📘journal: MACHINE LEARNING AND KNOWLEDGE EXTRACTION
🗓Publish year: 2020
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #Learning #Extracting #Graph #Features #Link_Prediction #review
📘journal: MACHINE LEARNING AND KNOWLEDGE EXTRACTION
🗓Publish year: 2020
📎Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #Learning #Extracting #Graph #Features #Link_Prediction #review
👍1