CSoNet 2021 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 2021 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 The conference solicits theoretical, methodological, empirical, and experimental research reporting original and unpublished results on computational big data and social networks.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 2021. 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
Long Le, University of Quebec
Jun Pei, Hefei University of Technology
Ruoming Jin, Kent State University
David Mohaisen, University of Central Florida
Abstract Submission June 6, 2021
Paper Submission June 20, 2021
Acceptance Notification September 10, 2021
Camera Ready & Registration September 24, 2021
Conference Dates November 15-17, 2021
Conference Mode of Operation:
The conference is planned as an in-person conference, allowing those who cannot be present in person to attend and present virtually. Depending on the development of COVID-19 and the vaccination, the mode of the conference will be revised accordingly.
More Information about the conference and the organizers is available at http://optnetsci.cise.ufl.edu/CSoNet/