Overview

The Annual Meeting of the International Society for Data Science and Analytics (ISDSA) aims to provide a global forum for researchers and practitioners in the field of data science and data analytics to communicate and showcase their latest research. The ISDSA Meeting is for anyone interested in data science and data analytics. Researchers, practitioners, educators, and users come together at the ISDSA Meeting to present new and ongoing work and to discuss future directions for data science and data analytics.

The 2023 Annual Meeting of ISDSA will take place in Shanghai, China. The theme of the 2023 meeting is Applied Data Science.

We particularly welcome submission on the following two topics.

  • Data Science in Humanities and Social Sciences. Selected papers will be published in the Springer journal Fudan Journal of the Humanities and Social Sciences (Q2; Citescore 2021 is 1.9 and ranks 91 out of 264 journals in in General Social Sciences category).
  • Data Science Methods in Political Science and Public Policy Research. Selected papers will be published in the Springer journal Chinese Political Science Review (Q1; Citescore 2021 is 2.1 and ranks 147 out of 608 journals in Political Science and International Relations category).

Abstract submission is open till March 15, 2023 and accpetance decision is typically made one week after submission and no late than April 15, 2023.

We also offer 6 workshops:

  • Workshop 1: Introduction to Social Network Analysis by Prof. Haiyan Liu, University of California, Merced
  • Workshop 2: Longitudinal Data Analysis (In Chinese) by Prof. Hongyun Liu, Beijing Normal University
  • Workshop 3: Practical Mediation Analysis by Prof. Laura Lu, University of Georgia and Prof. Qian Zhang, Florida State University
  • Workshop 4: Deep Learning Using R by Prof. Zhiyong Zhang, University of Notre Dame
  • Workshop 5: From Latent Class Model to Latent Transition Model Using Mplus (In Chinese) by Prof. Hawjeng Chiou, National Taiwan Normal University
  • Workshop 6: Bayesian Longitudinal Data Modeling by Prof. Cynthia Tong from University of Virginia

 

Help ISDSA

ISDSA is an exempt organization under section 501(c)(3) of the Internal Revenue Code. Please make a tax deductible contribution to ISDSA. All the contributions will be used to support researchers and students to attend the ISDSA meetings.