Conference Information
CSoNet 2023: International Conference on Computational Data and Social Networks
https://csonet-conf.github.io/csonet23/index.html
Submission Date:
2023-09-05
Notification Date:
2023-11-05
Conference Date:
2023-12-11
Location:
Hanoi, Vietnam
Years:
12
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Call For Papers
CSoNet 2023 provides a premier interdisciplinary forum to bring together researchers and practitioners from all fields of big data networks, such as billion-scale network computing, data network analysis, mining, security and privacy, and deep learning. CSoNet 2023 seeks to address emerging yet important computational problems, with a focus on the fundamental background, theoretical technology development, and real-world applications associated with big data network analysis, modeling, and deep learning. The conference solicits theoretical, methodological, empirical, and experimental research reporting original and unpublished results on computational big data networks. The conference will be organized in Hanoi, Vietnam.

Topics of interest include, but are not limited to:

    Real-world Complex Networks Analysis
    Trends and Pattern Analysis in Social Networks
    Representation Learning on Networks
    Big Data Analysis
    Mathematical Modeling and Analysis of Real-world Networks
    Network Structure Analysis and Dynamics Optimization
    Data Network Design and Architecture
    Information Diffusion Models and Techniques
    Security and Privacy in Data Networks
    Efficient Algorithms for Large-scale Data Networks Computing
    Reputation and Trust in Social Media
    Social Influence, Recommendation, and Media
    Energy Efficiency in Mobile Data Networks
    Natural Language Understanding for Network Analysis
    E-commerce and Social Media Marketing
    Deep Learning on Graphs and its Application
    Stock Market Prediction and Stock Recommendation
    Anomaly Detection, Security, and Privacy in Big Data Networks
    Analysis of signed and attributed real-world networks
    Multidimensional graph analysis
    Algorithmic fairness in network analysis and graph mining
Last updated by Dou Sun in 2023-09-01
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