Information Equilibrium Maximization Problem in Social Networks Based on Entropy

IF 7.9 2区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY

IEEE Transactions on Network Science and Engineering Pub Date : 2025-03-16 DOI:10.1109/TNSE.2025.3571165

Runzhi Li;Jianming Zhu;Guoqing Wang

{"title":"Information Equilibrium Maximization Problem in Social Networks Based on Entropy","authors":"Runzhi Li;Jianming Zhu;Guoqing Wang","doi":"10.1109/TNSE.2025.3571165","DOIUrl":null,"url":null,"abstract":"Personal cognition, product advertising and social recommendations are important factors to develop brand preferences, which directly influence consumer purchasing behaviors. A diversified brand preference landscape is conductive to preventing market monopolization, thus promoting healthier market competition. The entry of a new brand enhances market diversity and contributes to equilibrium of consumers' brand preferences. The new entrant stimulates competitive responses from incumbent brands because of catfish effect. Then market shares undergo redistribution as all brands increase their operational vitality in response to the competitive pressure. To select <inline-formula><tex-math>$k$</tex-math></inline-formula> users in a social network as advertisers of a new brand, this paper proposes the information equilibrium maximization (IEM) problem, and proves that the IEM is NP-hard, computing the objective function is #P-hard, and the objective function is neither modular nor monotonic. Then the entropy-based equilibrium degree maximization (EEDM) algorithm is proposed. In experiments, based on three methods of selecting seed nodes, E_qedm shows its superiority. It has strong robustness when the size of seedsets is large enough, and activation probability and update probability are more than 0.5. Besides, the number of initial preferences has little influence on the performance of E_qedm.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 5","pages":"4287-4298"},"PeriodicalIF":7.9000,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Network Science and Engineering","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/11006381/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}

引用次数: 0

Abstract

Personal cognition, product advertising and social recommendations are important factors to develop brand preferences, which directly influence consumer purchasing behaviors. A diversified brand preference landscape is conductive to preventing market monopolization, thus promoting healthier market competition. The entry of a new brand enhances market diversity and contributes to equilibrium of consumers' brand preferences. The new entrant stimulates competitive responses from incumbent brands because of catfish effect. Then market shares undergo redistribution as all brands increase their operational vitality in response to the competitive pressure. To select

$k$

users in a social network as advertisers of a new brand, this paper proposes the information equilibrium maximization (IEM) problem, and proves that the IEM is NP-hard, computing the objective function is #P-hard, and the objective function is neither modular nor monotonic. Then the entropy-based equilibrium degree maximization (EEDM) algorithm is proposed. In experiments, based on three methods of selecting seed nodes, E_qedm shows its superiority. It has strong robustness when the size of seedsets is large enough, and activation probability and update probability are more than 0.5. Besides, the number of initial preferences has little influence on the performance of E_qedm.

查看原文本刊更多论文

基于熵的社会网络信息均衡最大化问题

个人认知、产品广告和社会推荐是形成品牌偏好的重要因素，直接影响消费者的购买行为。多元化的品牌偏好格局有利于防止市场垄断，从而促进更健康的市场竞争。新品牌的进入增强了市场的多样性，有助于消费者品牌偏好的均衡。由于鲶鱼效应，新进入者刺激了现有品牌的竞争反应。然后，市场份额再分配，因为所有品牌都增加了经营活力，以应对竞争压力。为了在社交网络中选择$k$用户作为新品牌的广告客户，本文提出了信息均衡最大化问题，并证明了信息均衡最大化是np困难的，目标函数的计算是# p困难的，目标函数既不是模块化的，也不是单调的。然后提出了基于熵的均衡度最大化算法。在实验中，基于三种选择种子节点的方法，E_qedm显示出其优越性。当种子集的大小足够大，激活概率和更新概率均大于0.5时，具有较强的鲁棒性。此外，初始偏好的数量对E_qedm的性能影响不大。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

IEEE Transactions on Network Science and Engineering Engineering-Control and Systems Engineering

CiteScore

12.60

自引率

9.10%

发文量

393

期刊介绍： The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.