首页|Source localization in signed networks with effective distance

Source localization in signed networks with effective distance

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While progress has been made in information source localization,it has overlooked the prevalent friend and adver-sarial relationships in social networks.This paper addresses this gap by focusing on source localization in signed network models.Leveraging the topological characteristics of signed networks and transforming the propagation probability into effective distance,we propose an optimization method for observer selection.Additionally,by using the reverse prop-agation algorithm we present a method for information source localization in signed networks.Extensive experimental results demonstrate that a higher proportion of positive edges within signed networks contributes to more favorable source localization,and the higher the ratio of propagation rates between positive and negative edges,the more accurate the source localization becomes.Interestingly,this aligns with our observation that,in reality,the number of friends tends to be greater than the number of adversaries,and the likelihood of information propagation among friends is often higher than among ad-versaries.In addition,the source located at the periphery of the network is not easy to identify.Furthermore,our proposed observer selection method based on effective distance achieves higher operational efficiency and exhibits higher accuracy in information source localization,compared with three strategies for observer selection based on the classical full-order neighbor coverage.

complex networkssigned networkssource localizationeffective distance

马志伟、孙蕾、丁智国、黄宜真、胡兆龙

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Zhejiang Normal University,School of Computer Science and Technology,Jinhua 321004,China

Shanghai Business School,School of Business and Economics,Shanghai 200235,China

Jinhua Polytechnic,School of Information Engineering,Jinhua 321016,China

National Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaZhejiang Provincial Philosophy and Social Science Planning ProjectEducation Ministry Humanities and Social Science Foundation of ChinaEducation Ministry Humanities and Social Science Foundation of ChinaNatural Science Foundation of Zhejiang Province of ChinaNatural Science Foundation of Zhejiang Province of China

621033756200610622NDJC009Z19YJCZH05621YJC630120LY23F030003LQ21F020005

2024

10.1088/1674-1056/ad1482

中国物理B(英文版)
中国物理学会和中国科学院物理研究所

中国物理B(英文版)

CSTPCDEI
影响因子：0.995
ISSN：1674-1056
年,卷(期)：2024.33(2)
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