Abstract
In social networks, the departure of some users can lead to the drop-out of others in cascade. Therefore, the engagement of critical users can significantly influence the stability of a network. In the literature, the anchored k-core problem is proposed, which aims to enlarge the community by anchoring b nodes. While, in real social networks, nodes are usually associated with different preferences, i.e., inclination, such as close or conflict interest. Intuitively, a community will be more stable if more nodes have close interest and fewer of them carry conflict interest. However, most existing researches simply treat all users equally, and the inclination property is neglected. To fill the gap, in this paper, we propose and investigate the inclined anchored k-core problem, which aims to anchor b nodes, such that more close nodes and fewer conflict nodes will join the community. We show that this problem is NP-hard. To facilitate the computation, a layer-based searching framework is adopted. In addition, an upper bound based technique is developed to enable early termination in iterations. Comprehensive experiments and case studies are conducted on 9 networks to demonstrate the effectiveness and efficiency of the proposed methods.
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Acknowledgments
Chen Chen, Xijuan Liu and Shuangyan Xu are joint first authors. This work is supported by NSFC 61802345, ZJNSF LQ20F020007, ZJNSF LY21F020012 and Y202045024.
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Chen, C., Liu, X., Xu, S., Zhang, M., Wang, X., Lin, X. (2021). Critical Nodes Identification in Large Networks: An Inclination-Based Model. In: Zhang, W., Zou, L., Maamar, Z., Chen, L. (eds) Web Information Systems Engineering – WISE 2021. WISE 2021. Lecture Notes in Computer Science(), vol 13080. Springer, Cham. https://doi.org/10.1007/978-3-030-90888-1_35
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DOI: https://doi.org/10.1007/978-3-030-90888-1_35
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