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Social activity matching with graph neural network in event-based social networks

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Abstract

In recent years, event-based social networks (EBSNs) have become increasingly popular. Different from traditional online social networks, EBSNs consist of valuable online and offline social interactions, which can bring users more experience and entertainment. One of the crucial tasks for the EBSN platforms is to match users and social activities to help users participate in suitable activities. However, the existing matching methods either do not consider the influence of adjacent activities and users and the processing of newly added activities, or ignore the actual attribute constraints, e.g., budget and capacity. To address the limitations, we propose a novel graph neural network-based social activity matching method. Specifically, we model the historical records with a heterogeneous graph, and connect any new activity node to the user node who is the organizer. We then design a neural network-based affinity calculation model to predict the affinities between users and new activities. Moreover, we use a greedy-based heuristic method for social activity matching, considering the bilateral constraints extracted from the user and the activity attributes. Extensive experiments on three real event-based social service datasets show the effectiveness of the proposed method, which outperforms the state-of-the-art baselines in terms of affinity prediction and social activity matching.

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Data Availability

The datasets analyzed during the current study are available in the Ref [19].

Notes

  1. http://www.meetup.com/.

  2. http://plancast.com-based.

  3. https://beijing.douban.com.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (NSFC) (Grants Nos. U19A2061, 62206105, and 61772228), National Key Research and Development Program of China under Grant No. 2017YFC1502306, China Postdoctoral Science Foundation funded project under Grant No. 2021M701388.

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Authors and Affiliations

  1. College of Computer Science and Technology, Jilin University, Changchun, 130012, Jilin, China

    Bingyi Sun, Xiaohui Wei, Jiaxu Cui & Yan Wu

  2. Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education, University, Changchun, 130012, Jilin, China

    Bingyi Sun, Xiaohui Wei, Jiaxu Cui & Yan Wu

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  1. Bingyi Sun
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  2. Xiaohui Wei
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  3. Jiaxu Cui
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Correspondence to Jiaxu Cui.

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Sun, B., Wei, X., Cui, J. et al. Social activity matching with graph neural network in event-based social networks. Int. J. Mach. Learn. & Cyber. 14, 1989–2005 (2023). https://doi.org/10.1007/s13042-022-01741-1

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