Quantifying Node Importance over Network Structural Stability

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Abstract

Quantifying node importance on engagement dynamics is critical to support network stability. We can motivate or retain the users in a social platform according to their importance s.t. the network is more sustainable. Existing studies validate that the coreness of a node is the "best practice"on network topology to estimate the engagement of the node. In this paper, the importance of a node is the effect on the engagement of other nodes when its engagement is strengthened or weakened. Specifically, the importance of a node is quantified via two novel concepts: the anchor power to measure the engagement effect of node strengthening (i.e., the overall coreness gain) and the collapse power to measure the engagement effect of node weakening (i.e., the overall coreness loss). We find the computation of the two concepts can be naturally integrated into a shell component-based framework, and propose a unified static algorithm to compute both the anchored and collapsed followers. For evolving networks, efficient maintenance techniques are designed to update the follower sets of each node, which is faster than redoing the static algorithm by around 3 orders of magnitude. Extensive experiments on real-life data demonstrate the effectiveness of our model and the efficiency of our algorithms.

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Zhang, F., Linghu, Q., Xie, J., Wang, K., Lin, X., & Zhang, W. (2023). Quantifying Node Importance over Network Structural Stability. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 3217–3228). Association for Computing Machinery. https://doi.org/10.1145/3580305.3599480

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