This work is licensed under the Creative Commons Attribution 4.0 International License.
China Internet Network Information Center. The 47th Statistical Report on Internet Development in China. Beijing: China Network Information Center, 2020China Internet Network Information CenterBeijingChina Network Information Center2020Search in Google Scholar
Abdulaziz Elwalda, Kevin Lü, Maged Ali. Perceived derived attributes of online customer reviews. Computers in Human Behavior, 2016, 56(1), pp. 306–319.ElwaldaAbdulazizLüKevinAliMagedPerceived derived attributes of online customer reviews2016561306319Search in Google Scholar
Yi-Hsiu Cheng, Hui-Yi Ho. Social influence's impact on reader perceptions of online reviews. Journal of Business Research, 2015, 68(3), PP. 883–887.ChengYi-HsiuHoHui-YiSocial influence's impact on reader perceptions of online reviews2015683883887Search in Google Scholar
JINDAL N, LIU B., Opinion spam and analysis. Proceedings of the 2008 International Conference on Web Search and Data Mining. New York: ACM, 2008, PP. 219–230.JINDALNLIUBProceedings of the 2008 International Conference on Web Search and Data MiningNew York: ACM2008219230Search in Google Scholar
Banerjee S, Chua A Y K. Understanding the process of writing fake online reviews. Ninth International Conference On Digital Information Management. Phitsanulok, Thailand, 2014, pp. 68–73.BanerjeeSChuaA Y KNinth International Conference On Digital Information ManagementPhitsanulok, Thailand20146873Search in Google Scholar
Chang T, Hsu P Y, Cheng M S, et al., Detecting Fake Review with Rumor Model-Case Study in Hotel Review. Intelligence Science and Big Data Engineering. Big Data and Machine Learning Techniques. Springer International Publishing, 2015, PP. 181–192.ChangTHsuP YChengM SDetecting Fake Review with Rumor Model-Case Study in Hotel ReviewSpringer International Publishing2015181192Search in Google Scholar
Lim E P, Nguyen V A, Jindal N, et al. Detecting product review spammers using rating behaviors. Proceedings of the 19th ACM Conference on Information and Knowledge Management, CIKM 2010, Toronto, Ontario, Canada: ACM, 2010, PP. 939–948.LimE PNguyenV AJindalNProceedings of the 19th ACM Conference on Information and Knowledge Management, CIKM 2010Toronto, Ontario, Canada: ACM2010939948Search in Google Scholar
Zeng Zhiyuan, Lu Xiaoyong, Xu Shengjian, et al. Spam review detection base on deep learning model of multi-layer attention mechanism. Computer Application and Software, 2020, 37(5), PP. 177–182ZengZhiyuanLuXiaoyongXuShengjianSpam review detection base on deep learning model of multi-layer attention mechanism2020375177182Search in Google Scholar
Mukherjee A, Kumar A, Liu B, et al. Spotting opinion spammers using behavioral footprints. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Chicago, IL, USA: ACM, 2013, PP. 632–640.MukherjeeAKumarALiuBACM SIGKDD International Conference on Knowledge Discovery and Data MiningChicago, IL, USA: ACM2013632640Search in Google Scholar
Li H, Fei G, Wang S, et al. Bimodal distribution and co-bursting in review spam detection. Proceedings of the 26th International Conference on World Wide Web. International World Wide Web Conferences Steering Committee. Perth, Australia: ACM, 2017, PP. 1063–1072.LiHFeiGWangSProceedings of the 26th International Conference on World Wide Web. International World Wide Web Conferences Steering CommitteePerth, Australia: ACM201710631072Search in Google Scholar
Akoglu L, Chandy R, Faloutsos C. Opinion fraud detection in online reviews by network effects. Seventh international AAAI conference on weblogs and social media. Cambridge: AAAI, 2013, PP. 1–10.AkogluLChandyRFaloutsosCSeventh international AAAI conference on weblogs and social mediaCambridge: AAAI2013110Search in Google Scholar
Rayana S, Akoglu L. Collective Opinion Spam Detection: Bridging Review Networks and Metadata. Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Sydney, NSW, Australia: ACM, 2015, pp. 985–994.RayanaSAkogluLProceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data MiningSydney, NSW, Australia: ACM2015985994Search in Google Scholar
Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks. International Conference on Neural Information Processing Systems. Curran Associates Inc. 2012, PP. 1097–1105.KrizhevskyASutskeverIHintonG EInternational Conference on Neural Information Processing SystemsCurran Associates Inc.201210971105Search in Google Scholar
Graves A. Supervised Sequence Labelling with Recurrent Neural Networks. Springer Berlin Heidelberg, 2012, 385.GravesASpringerBerlin Heidelberg2012385Search in Google Scholar
Chung J, Gulcehre C, Cho K H, et al. Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling. Eprint Arxiv, 2014.ChungJGulcehreCChoK HEmpirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling2014Search in Google Scholar
Abadi M, Agarwal A, Barham P, et al. TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems. 2015.AbadiMAgarwalABarhamP2015Search in Google Scholar
Xu B, Wang N, Chen T, et al. Empirical Evaluation of Rectified Activations in Convolutional Network. Computer Science, 2015.XuBWangNChenTEmpirical Evaluation of Rectified Activations in Convolutional Network2015Search in Google Scholar