Epj Data Science

杂志介绍

Epj Data Science杂志介绍

《Epj Data Science》是一本以English为主的开放获取国际优秀期刊，中文名称Epj 数据科学，本刊主要出版、报道计算机科学-MATHEMATICS, INTERDISCIPLINARY APPLICATIONS领域的研究动态以及在该领域取得的各方面的经验和科研成果，介绍该领域有关本专业的最新进展，探讨行业发展的思路和方法，以促进学术信息交流，提高行业发展。该刊已被国际权威数据库SCIE、SSCI收录，为该领域相关学科的发展起到了良好的推动作用，也得到了本专业人员的广泛认可。该刊最新影响因子为3，最新CiteScore 指数为6.1。

本刊近期中国学者发表的论文主要有：

• Segregation in religion networks

  Author: Jiantao Hu, Qian-Ming Zhang, Tao Zhou

• Individual position diversity in dependence socioeconomic networks increases economic output

  Author: Wen-Jie Xie, Yan-Hong Yang, Ming-Xia Li, Zhi-Qiang Jiang, Wei-Xing Zhou

• Measuring economic activity in China with mobile big data

  Author: Lei Dong, Sicong Chen, Yunsheng Cheng, Zhengwei Wu, Chao Li, Haishan Wu

• Comparison of traffic reliability index with real traffic data

  Author: Limiao Zhang, Guanwen Zeng, Shengmin Guo, Daqing Li, Ziyou Gao

英文介绍

Epj Data Science杂志英文介绍

EPJ Data Science covers a broad range of research areas and applications and particularly encourages contributions from techno-socio-economic systems, where it comprises those research lines that now regard the digital “tracks” of human beings as first-order objects for scientific investigation. Topics include, but are not limited to, human behavior, social interaction (including animal societies), economic and financial systems, management and business networks, socio-technical infrastructure, health and environmental systems, the science of science, as well as general risk and crisis scenario forecasting up to and including policy advice.