Dear Colleagues,
I'd like to bring your attention to the July 2022 issue of the Journal
of Data Science (https://jds-online.org), a special issue on Data
Science Meets Social Sciences guest edited by:
+ Elena A. Erosheva, Department of Statistics, School of Social Work,
and the Center for Statistics and the Social Sciences, University of
Washington
+ Shahryar Minhas, Department of Political Science, Michigan State University
+ Gongjun Xu, Department of Statistics, University of Michigan
+ Ran Xu, Department of Allied Health Sciences, University of Connecticut
Congratulations to the authors, reviewers, and guest-editors!
All the articles are published under the CC-BY license
(https://creativecommons.org/licenses/by/4.0/) for the widest
dissemination. Funded by the School of Statistics and the Center for
Applied Statistics, Renmin University of China, there are no Article
Processing Charges. The journal features a fast review process and
reproducibility check.
Established in 2003, the Journal of Data Science aims to advance and
promote data science methods, computing, and applications in all
scientific fields where knowledge and insights are to be extracted
from data. We welcome submissions to all the sections including 1)
Philosophies of Data Science; 2) Statistical Data Science; 3)
Computing in Data Science; 4) Data Science in Action; 5) Data Science
Review; 6) Education in Data Science.
Best regards.
Jun Yan
Editor, Journal of Data Science
===
Journal of Data Science
Volume 20, Issue 3 (2022): Special Issue: Data Science Meets Social
Sciences, July 2022
Editorial: Data Science Meets Social Sciences
Elena A. Erosheva, Shahryar Minhas, Gongjun Xu, Ran Xu
https://doi.org/10.6339/22-JDS203EDIPub. online: 21 Jul 2022 Type: Editorial Open Access
pp. 277–278
Hypothesis Testing for Hierarchical Structures in Cognitive Diagnosis Models
Chenchen Ma, Gongjun Xu
https://doi.org/10.6339/21-JDS1024Pub. online: 14 Oct 2021 Type: Statistical Data Science Open Access
pp. 279–302
Is the Group Structure Important in Grouped Functional Time Series?
Yang Yang, Han Lin Shang
https://doi.org/10.6339/21-JDS1031Pub. online: 4 Jan 2022 Type: Statistical Data Science Open Access
pp. 303–324
Bayesian Inference for Spatial Count Data that May be Over-Dispersed
or Under-Dispersed with Application to the 2016 US Presidential
Election
Hou-Cheng Yang, Jonathan R. Bradley
https://doi.org/10.6339/21-JDS1032Pub. online: 29 Dec 2021 Type: Statistical Data Science Open Access
pp. 325–337
Improving the Science of Annotation for Natural Language Processing:
The Use of the Single-Case Study for Piloting Annotation Projects
Kylie Anglin, Arielle Boguslav, Todd Hall
https://doi.org/10.6339/22-JDS1054Pub. online: 8 Jul 2022 Type: Data Science In Action Open Access
pp. 339–357
Tree-Based Methods: A Tool for Modeling Nonlinear Complex
Relationships and Generating New Insights from Data
Ya Mo, Brian Habing, Nell Sedransk
https://doi.org/10.6339/22-JDS1056Pub. online: 18 Jul 2022 Type: Data Science In Action Open Access
pp. 359–379
Do Americans Think the Digital Economy is Fair? Using Supervised
Learning to Explore Evaluations of Predictive Automation
Emilio Lehoucq
https://doi.org/10.6339/22-JDS1053Pub. online: 20 Jun 2022 Type: Data Science In Action Open Access
pp. 381–399
Does Aging Make Us Grittier? Disentangling the Age and Generation
Effect on Passion and Perseverance
Shane Sanders, Nuwan Indika, Millagaha Gedara, Bhavneet Walia,
Christopher Boudreaux, Merril Silverstein
https://doi.org/10.6339/22-JDS1041Pub. online: 14 Apr 2022 Type: Data Science In Action Open Access
pp. 401–411
Econometrics at Scale: Spark up Big Data in Economics
Benjamin Bluhm, Jannic Alexander Cutura
https://doi.org/10.6339/22-JDS1035Pub. online: 7 Apr 2022 Type: Data Science Reviews Open Access
pp. 413–436