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Dynamic knowledge graph based fake-review detection

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Abstract

Online product reviews are an important driver of customers’ purchasing behavior. Fake reviews seriously mislead consumers, challenging the fairness of the online shopping environment. Although the detection of fake reviews has progressed, several problems remain. First, fake comment recognition ignores the correlation between time and the semantics of the comment texts, which is always hidden in the context of the reviews. Second, the impact of multi-source information on fake comment recognition is not considered, as it constitutes a complex, high-dimensional, heterogeneous relationship between reviewers, reviews, stores and commodities. To overcome these problems, the present paper proposes a dynamic knowledge graph-based method for fake-review detection. Based on the characteristics of online product reviews, it first extracts four types of entities using a developed neural network model called sentence vector/twin-word embedding conditioned bidirectional long short-term memory. Time series related features are then added to the knowledge graph construction process, forming dynamic graph networks. To enhance the fake-review detection, four indicators are newly defined for determining the relationships among the four types of nodes. In experimental evaluations, our method surpassed the state-of-the-art results.

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Acknowledgments

The work is partially supported by the National Natural Science Foundation of China (Nos.61672329, 61373149, 61472233, 61572300, 81273704), Shandong Province Science and Technology Plan Supported Project (No.2014GGX101026) and Taishan Scholar Fund of Shandong Province (No.TSHW201502038, 20110819). We also gratefully acknowledge the support of NVIDIA Corporation with the donation of the TITAN X GPU used for this research.

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Authors and Affiliations

  1. School of Information Science and Engineering, Shandong Normal University, Jinan, 250014, Shandong, China

    Youli Fang, Hong Wang, Lili Zhao, Fengping Yu & Caiyu Wang

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  1. Youli Fang
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  2. Hong Wang
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  3. Lili Zhao
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  4. Fengping Yu
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  5. Caiyu Wang
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Correspondence to Hong Wang.

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Fang, Y., Wang, H., Zhao, L. et al. Dynamic knowledge graph based fake-review detection. Appl Intell 50, 4281–4295 (2020). https://doi.org/10.1007/s10489-020-01761-w

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