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Selecting Influential Nodes in Social Networks Using Neighborhood Coreness

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Abstract

With the proliferation of social networks, the study of the spread of influence has grabbed the attention of researchers from various disciplines. Finding a subset of nodes in a social network that maximizes the spread of influence in the network is called the Influence Maximization Problem (IMP). One of the important applications is viral marketing, which finds influential people to promote a new product on social networks. Other applications include information distribution, preventing the spread of epidemic outbreaks, etc. The IMP has been shown as NP-hard, and several approximation algorithms and heuristics have been proposed in the literature. The heuristics based on classical centrality measures and methods based on k-shell and k-core have shown significant performance improvement. Recently, methods like Voterank and Voterank++ based on the voting scheme have been proposed in which voting ability and voting score computations are based on the degree of the node and its neighbors. However, it is observed that not only the degree but the topological location of the nodes also plays a role in influence spread. We propose a method NCVoterank++ based on a voting-based approach and Neighborhood Coreness for identifying influential nodes. We have experimented on several datasets to evaluate our proposed method using the Susceptible–Infected–Recovered (SIR) model. Our method, NCVoterank++, performs better in most cases regarding spreading speed and final infected scale than other existing algorithms.

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Data availability

Publicly available datasets were analyzed in this study. This data can be found here: http://konect.cc/networks/, https://snap.stanford.edu/data/.

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Authors and Affiliations

  1. School of Computer and Information Sciences, University of Hyderabad, Hyderabad, Telangana, 500046, India

    N. Govind & Rajendra Prasad Lal

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  1. N. Govind
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  2. Rajendra Prasad Lal
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This article is part of the topical collection “Research Trends in Communication and Network Technologies” guest edited by Anshul Verma, Pradeepika Verma and Kiran Kumar Pattanaik.

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Govind, N., Lal, R.P. Selecting Influential Nodes in Social Networks Using Neighborhood Coreness. SN COMPUT. SCI. 5, 100 (2024). https://doi.org/10.1007/s42979-023-02416-6

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