The 11th International Conference on Computational Data and Social Networks

CSoNet 2022


Software Systems Theoretical Computer Science



Dear Colleagues,
** Please accept our apologies if you receive multiple copies of this CFP **
CSoNet 2022 provides a premier interdisciplinary forum to bring together researchers and practitioners from all fields of big data and social networks, such as billion-scale network computing, social network/media analysis, mining, security and privacy, and deep learning and applications. CSoNet 2022 seeks to address emerging yet important computational problems, with a focus on the fundamental background, theoretical developments, and real-world applications associated with big data network analysis, modelling, and deep learning and understanding. The conference solicits theoretical, methodological, empirical, and experimental research reporting original and unpublished results on computational big data and social networks. 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 Social Platforms
Network Structure Analysis and Dynamics Optimization
Data Network Design and Architecture
Information Diffusion Models and Techniques
Security and Privacy in Data Networks and Analysis
Efficient Algorithms for Large-scale Data Networks Computing
Reputation and Trust in Social Media
Social Influence, Recommendation, and Media
Applications of Complex Data Network Analysis
Energy Efficiency in Mobile Data Networks
Natural Language Understanding and Applications for Social Media
E-commerce and Social Media Marketing
Deep Learning on Graphs and its Applications
Stock Market Prediction and Stock Recommendation with Social Media Data
Anomaly Detection, Security, and Privacy in Big Data Networks
Analysis of Signed and Attributed Real-world Networks
Multidimensional Graph Analysis
Algorithmic Fairness in Social Network Analysis and Graph Mining.
Socially-relevant Analytics from Social Media Contents (e.g., Bias, Toxicity, etc.)
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 the Journal of Combinatorial Optimization, IEEE Transactions on Network Science and Engineering, and Computational Social Networks.
Authors who are interested in the above topics can submit their unpublished work to CSoNet 2022. A clear indication of the motivation and comparison with prior related work should be presented. Simultaneous submission to a journal or another conference with refereed proceedings is not allowed.
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.
Proofs omitted due to space constraints must be placed in an appendix to be read by the program committee members at their discretion.
Submission link: https://easychair.org/conferences/?conf=csonet2021
Organizing Committee
General Chair
Xiaofeng Gao
Shanghai JiaoTong University
Program Co-chairs
Minming Li, City University of Hong Kong
Thang N. Dinh, Virginia Commonwealth University
Publicity Chair
Qin Hu
Indiana University–Purdue University Indianapolis
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
Important Dates:
Paper Submission August 14, 2022
Acceptance Notification September 10, 2022
Camera Ready & Registration September 24, 2022
Conference Dates December 5-7, 2022
Conference Mode of Operation:
The conference is planned as a fully virtual conference. More Information about the conference and the organizers is available at http://optnetsci.cise.ufl.edu/CSoNet/