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Social Network Analysis and Mining

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01.12.2020 | Original Article

Efficient influence spread estimation for influence maximization

verfasst von: Zahra Aghaee, Sahar Kianian

Erschienen in: Social Network Analysis and Mining | Ausgabe 1/2020

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Abstract

Word-of-Mouth promotion is among the effective methods of marketing and is highly regarded by many commercial companies. This type of marketing is mapped on the influence maximization problem (IMP) in the social networks, and its goal is finding a specific set of the individuals with the maximum influence on the network. Therefore, in this paper, a heuristic-greedy algorithm named the HEDVGreedy algorithm was proposed for the IMP in the social networks. In this algorithm, the expected diffusion value of the graph nodes was calculated using the heuristic method, and then, the effective nodes were selected using the greedy method. Experimental results showed that the proposed algorithm has a high performance than the baseline algorithms while, it significantly reduces the running time of the computations under both the Independent Cascade and Weighted Cascade models in the eight real-world data sets.

Vorheriger Artikel Stability of network centrality measures: a numerical study

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Titel: Efficient influence spread estimation for influence maximization
verfasst von: Zahra Aghaee
Sahar Kianian
Publikationsdatum: 01.12.2020
Verlag: Springer Vienna
Erschienen in: Social Network Analysis and Mining / Ausgabe 1/2020
Print ISSN: 1869-5450
Elektronische ISSN: 1869-5469
DOI: https://doi.org/10.1007/s13278-020-00694-z

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