activity
20142023
most citedReconstructing propagation networks with natural diversity and identifying hidden sources

219 citations · 707 across the 13 of their papers we have counts for

collaborators

13 papers

cs.DL2023★ 2 cited

Two indicators rule them all: Mean and standard deviation used to calculate other journal indicators based on log-normal distribution of citation counts

Zhesi Shen, Liying Yang, Jinshan Wu

Two journal-level indicators, respectively the mean () and the standard deviation () are proposed to be the core indicators of each journal and we show that quite several…

cs.DL2023

Analyzing Journal Category Assignment Using a Paper-level Classification System: Multidisciplinary Sciences Journals

Jiandong Zhang, Liying Yang, Zhesi Shen

In the field of scientometrics, the subject classification system of academic journals holds great importance. Accurate identification and classification of "multidisciplinary" jou…

physics.soc-ph2021★ 1 cited

Control core of undirected complex networks

Zhengzhong Yuan, Jingwen Li, Chen Zhao +2

With the development of complex networks, many researchers have paid greater attention to studying the control of complex networks over the last decade. Although some theoretical b…

cs.DL2020★ 3 cited

Novel utilization of a paper-level classification system for the evaluation of journal impact: An update of the CAS Journal Ranking

Sichao Tong, Fuyou Chen, Liying Yang +1

Since its first release in 2004, the CAS Journal Ranking, a ranking system of journals based on a citation impact indicator, has been widely used both in selecting journals when su…

cs.DL2020★ 1 cited

The effect of national and international multiple affiliations on citation impact

Sichao Tong, Ting Yue, Zhesi Shen +1

Researchers affiliated with multiple institutions are increasingly seen in current scientific environment. In this paper we systematically analyze the multi-affiliated authorship a…

physics.soc-ph2018★ 146 cited

Increasing trend of scientists to switch between topics

An Zeng, Zhesi Shen, Jianlin Zhou +5

We analyze the publication records of individual scientists, aiming to quantify the topic switching dynamics of scientists and its influence. For each scientist, the relations amon…

physics.soc-ph2016★ 9 cited

Do Mathematicians, Economists and Biomedical Scientists Trace Large Topics More Strongly Than Physicists?

Menghui Li, Liying Yang, Huina ZHang +3

In this work, we extend our previous work on largeness tracing among physicists to other fields, namely mathematics, economics and biomedical science. Overall, the results confirm…

physics.soc-ph2015★ 38 cited

A universal data based method for reconstructing complex networks with binary-state dynamics

Jingwen Li, Zhesi Shen, Wen-Xu Wang +2

To understand, predict, and control complex networked systems, a prerequisite is to reconstruct the network structure from observable data. Despite recent progress in network recon…

physics.soc-ph2015

Fundamental building blocks of controlling complex networks: A universal controllability framework

Zhesi Shen, Wen-Xu Wang, Chen Zhao +1

To understand the controllability of complex networks is a forefront problem relevant to different fields of science and engineering. Despite recent advances in network controllabi…

physics.soc-ph2015★ 2 cited

Interrelations among scientific fields and their relative influence revealed by input-output analysis

Zhesi Shen, Liying Yang, Jiansuo Pei +7

In this paper, we try to answer two questions about any given scientific discipline: First, how important is each subfield and second, how does a specific subfield influence other…

physics.soc-ph2015★ 178 cited

Robust Reconstruction of Complex Networks from Sparse Data

Xiao Han, Zhesi Shen, Wen-Xu Wang +1

Reconstructing complex networks from measurable data is a fundamental problem for understanding and controlling collective dynamics of complex networked systems. However, a signifi…

physics.soc-ph2015★ 108 cited

Locating the source of diffusion in complex networks by time-reversal backward spreading

Zhesi Shen, Shinan Cao, Wen-Xu Wang +2

Locating the source that triggers a dynamical process is a fundamental but challenging problem in complex networks, ranging from epidemic spreading in society and on the Internet t…

physics.soc-ph2014★ 219 cited

Reconstructing propagation networks with natural diversity and identifying hidden sources

Zhesi Shen, Wen-Xu Wang, Ying Fan +2

Our ability to uncover complex network structure and dynamics from data is fundamental to understanding and controlling collective dynamics in complex systems. Despite recent progr…