CAOM: A community-based approach to tackle opinion maximization for social networks

Wang, Xingwei; Mao, Fubing; Lv, Jianhui; Cai, Yuliang; Huang, Min; Xu, Qingzheng

doi:10.1016/j.ins.2019.10.064

Cited by 28 publications

(9 citation statements)

References 23 publications

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“…Meanwhile, only the undergraduates' political opinions are collected. In addition, three previous researches, that is, CAOM, 10 IMGA 11 and LIDDE 12 are used as the benchmarks. CAOM is a community‐based approach which includes community detection, selection of candidate nodes and generation of seed nodes.…”

Section: Methodsmentioning

confidence: 99%

Smart opinion formation maximization to improve political education of undergraduates in Social Information‐Centric Networking

Liu

2021

Internet Technology Letters

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Social Information‐Centric Networking (SICN) is an integration of Social Network (SN) and ICN, which is a popular paradigm as most of contents in SN depend on the transmission and interaction of ICN. In SICN, the research on opinion formation maximization is very important. Therefore, this paper considers the scenario regarding the political education of undergraduates and proposes a heuristic opinion formation maximization algorithm, including two stages. (a) The opinion formation model is built based on individual intimacy and social influence. (b) In order to make sure the opinion formation maximization, the collaborative evolution model is built. By comparing with three latest researches, the proposed heuristic algorithm can save the required identification time by 0.379 hour, 0.687 hour and 0.889 hour respectively. The experimental results further demonstrate that the research on opinion formation maximization in SICN makes for the improvement on the political education of undergraduates.

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Section: Methodsmentioning

confidence: 99%

Smart opinion formation maximization to improve political education of undergraduates in Social Information‐Centric Networking

Liu

2021

Internet Technology Letters

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“…In an ecosystem, foragers that cooperate are friends, and those that compete are enemies [17]. In social networks [18]- [21], two individuals can be friendly or hostile to each other. In order to model this situation, signed graph is used to describe the cooperation and competition between agents, where there are positive and negative weights of edges.…”

Section: Introductionmentioning

confidence: 99%

Event-Triggered Control for Guaranteed-Cost Bipartite Formation of Multi-Agent Systems

2022

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This paper is concerned with event-triggered guaranteed-cost bipartite formation control of multi-agent systems with antagonistic interactions. In order to save the limited network communication bandwidth of multi-agent systems, event-triggered sampled-data transmission strategy is adopted. Event conditions are designed for both leader and followers to reduce the frequency of state transmission more effectively. According to the event-triggered sampled-data of the leader and followers, bipartite formation controllers are designed for followers. By using the event conditions and the Lyapunov method, the sufficient conditions for the realization of bipartite formation and guaranteed-cost bipartite formation are obtained in terms of linear matrix inequality, respectively. Finally, the effectiveness of the theoretical results is demonstrated by numerical examples.INDEX TERMS Multi-agent systems, guaranteed-cost, bipartite formation, antagonistic interactions, event-triggered sampling.

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“…Network science has been an emerging area in big data, cyberspace security, and artificial intelligence [1][2][3][4]. Many real-world networks are mixed, such as citation networks, web page link networks, e-mail networks, and information diffusion networks.…”

Section: Introductionmentioning

confidence: 99%

The Hermitian Kirchhoff Index and Robustness of Mixed Graph

Lin

Zhou

et al. 2021

Mathematical Problems in Engineering

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Large-scale social graph data poses significant challenges for social analytic tools to monitor and analyze social networks. The information-theoretic distance measure, namely, resistance distance, is a vital parameter for ranking influential nodes or community detection. The superiority of resistance distance and Kirchhoff index is that it can reflect the global properties of the graph fairly, and they are widely used in assessment of graph connectivity and robustness. There are various measures of network criticality which have been investigated for underlying networks, while little is known about the corresponding metrics for mixed networks. In this paper, we propose the positive walk algorithm to construct the Hermitian matrix for the mixed graph and then introduce the Hermitian resistance matrix and the Hermitian Kirchhoff index which are based on the eigenvalues and eigenvectors of the Hermitian Laplacian matrix. Meanwhile, we also propose a modified algorithm, the directed traversal algorithm, to select the edges whose removal will maximize the Hermitian Kirchhoff index in the general mixed graph. Finally, we compare the results with the algebraic connectivity to verify the superiority of the proposed strategy.

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CAOM: A community-based approach to tackle opinion maximization for social networks

Cited by 28 publications

References 23 publications

Smart opinion formation maximization to improve political education of undergraduates in Social Information‐Centric Networking

Smart opinion formation maximization to improve political education of undergraduates in Social Information‐Centric Networking

Event-Triggered Control for Guaranteed-Cost Bipartite Formation of Multi-Agent Systems

The Hermitian Kirchhoff Index and Robustness of Mixed Graph

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