activity
20102023
most citedEvents Determine Spreading Patterns: Information Transmission via Internal and External Influences on Social Networks

97 citations · 472 across the 27 of their papers we have counts for

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Showing physics.soc-phShow all

19 papers · 1 filter

physics.soc-ph2023★ 1 cited

A universal meta-heuristic framework for influence maximization in hypergraphs

Ming Xie, Xiu-Xiu Zhan, Chuang Liu +1

Influence maximization (IM) aims to select a small number of nodes that are able to maximize their influence in a network and covers a wide range of applications. Despite numerous…

physics.soc-ph2023

A hyper-distance-based method for hypernetwork comparison

Tao Xu, Xiaowen Xie, Zi-Ke Zhang +2

Hypernetwork is a useful way to depict multiple connections between nodes, making it an ideal tool for representing complex relationships in network science. In recent years, there…

physics.soc-ph2022★ 1 cited

Vital node identification in hypergraphs via gravity model

Xiao-Wen Xie, Xiu-Xiu Zhan, Zi-Ke Zhang +1

Hypergraphs that can depict interactions beyond pairwise edges have emerged as an appropriate representation for modeling polyadic relations in complex systems. With the recent sur…

physics.soc-ph2021

Effective Model Integration Algorithm for Improving Link and Sign Prediction in Complex Networks

Chuang Liu, Shimin Yu, Ying Huang +1

Link and sign prediction in complex networks bring great help to decision-making and recommender systems, such as in predicting potential relationships or relative status levels. M…

physics.soc-ph2021★ 36 cited

The Aging Effect in Evolving Scientific Citation Networks

Feng Hu, Lin Ma, Xiu-Xiu Zhan +4

The study of citation networks is of interest to the scientific community. However, the underlying mechanism driving individual citation behavior remains imperfectly understood, de…

physics.soc-ph2021★ 1 cited

Exploring the effect of social media and spatial characteristics during the COVID-19 pandemic in China

Xiu-Xiu Zhan, Kaiyue Zhang, Lun Ge +6

The declaration of COVID-19 as a pandemic has largely amplified the spread of related information on social media, such as Twitter, Facebook, and WeChat.Unlike the previous studies…