CSoNet 2023：The 12th International Conference on Computational Data and Social Networks
Website：https://csonet-conf.github.io/csonet23/index.html
Time: Dec 11, 2023 - Dec 13, 2023
Location：Hanoi, Vietnam
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 The conference solicits theoretical, methodological, empirical, and experimental research reporting original and unpublished results on computational big data networks.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 at the National Economics University in Hanoi, Vietnam.
Accepted papers will be published in Springer’s Lecture Notes in Computer Science, and indexed by ISI (CPCI-S, included in ISI Web of Science), EI Engineering Index (Compendex and Inspec databases), ACM Digital Library, DBLP, Google Scholar, MathSciNet, etc. Also, extended versions of selected best papers will be invited for publication in Journal of Combinatorial Optimization and IEEE Transactions on Network Science and Engineering.
**Topics
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
**Important Dates:
Paper Submission: September 19, 2023
Acceptance Notification: November 5, 2023
Camera Ready & Registration: November 15, 2023
Conference Dates: December 11-13, 2023
**Submission Guidelines
Submissions must adhere to the following guidelines:
Papers must be formatted using the LNCS format (ftp://ftp.springernature.com/cs-proceeding/llncs/llncs2e.zip) without altering margins or the font point.
The maximum length of a regular paper (including references) is 12 pages; 2 pages for an extended abstract.
**Organizations
General Co-chairs
Pham Hong Chuong – National Economics University
Sergiy Butenko – Texas A&M University
TPC Co-Chairs
Ha Minh Hoang – Phenikaa University
Xingquan Zhu – Florida Atlantic University
Publicity Co-Chairs
Nguyen Phi Le – Hanoi University of Science and Technology
Min Shi – Harvard University
Web Chair
Pham Van Canh – Phenikaa University
Local Committee Chair
To Trung Thanh – National Economics University
Dao Thanh Tung – National Economics University
Steering Committee
My T. Thai (Chair) – University of Florida
Kim-Kwang Raymond Choo – University of Texas at San Antonio
Zhi-Li Zhang – University of Minnesota
Weili Wu – University of Texas, Dallas
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