activity
20092021
most citedRanking spreaders by decomposing complex networks

449 citations · 1.6k across the 40 of their papers we have counts for

collaborators

40 papers

physics.soc-ph2021★ 1 cited

Maximizing spreading in complex networks with risk in node activation

Leyang Xue, Peng Zhang, An Zeng

It is widely acknowledged that the initial spreaders play an important role for the wide spreading of information in complex networks. Thus, a variety of centrality-based methods h…

cs.SI2020

Limits of PageRank-based ranking methods in sports data

Yuhao Zhou, Ruijie Wang, Yi-Cheng Zhang +2

While PageRank has been extensively used to rank sport tournament participants (teams or individuals), its superiority over simpler ranking methods has been never clearly demonstra…

physics.soc-ph2020★ 2 cited

The critical role of fresh teams in creating original and multi-disciplinary research

An Zeng, Ying Fan, Zengru Di +2

Teamwork is one of the most prominent features in modern science. It is now well-understood that the team size is an important factor that affects team creativity. However, the cru…

physics.soc-ph2020

Prediction Model Based on Integrated Political Economy System: The Case of US Presidential Election

Lingbo Li, Ying Fan, An Zeng +1

This paper studies an integrated system of political and economic systems from a systematic perspective to explore the complex interaction between them, and specially analyzes the…

physics.soc-ph2019★ 5 cited

Enhancing the long-term performance of recommender system

Leyang Xue, Peng Zhang, An Zeng

Recommender system is a critically important tool in online commercial system and provide users with personalized recommendation on items. So far, numerous recommendation algorithm…

physics.soc-ph2019★ 6 cited

Predictability of diffusion-based recommender systems

Peng Zhang, Leyang Xue, An Zeng

The recommendation methods based on network diffusion have been shown to perform well in both recommendation accuracy and diversity. Nowdays, numerous extensions have been made to…