{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T05:45:33Z","timestamp":1742967933650,"version":"3.40.3"},"publisher-location":"Cham","reference-count":28,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030638290"},{"type":"electronic","value":"9783030638306"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-63830-6_61","type":"book-chapter","created":{"date-parts":[[2020,11,18]],"date-time":"2020-11-18T10:10:30Z","timestamp":1605694230000},"page":"730-742","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Detecting Online Fake Reviews via Hierarchical Neural Networks and Multivariate Features"],"prefix":"10.1007","author":[{"given":"Chengzhi","family":"Jiang","sequence":"first","affiliation":[]},{"given":"Xianguo","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Aiyun","family":"Jin","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,11,19]]},"reference":[{"key":"61_CR1","unstructured":"Arjun, M., et al.: Fake review detection: classification and analysis of real and pseudo reviews. Technical Report (2013)"},{"key":"61_CR2","first-page":"1","volume":"2015","author":"D Bahdanau","year":"2015","unstructured":"Bahdanau, D., et al.: Neural machine translation by jointly learning to align and translate. ICLR 2015, 1\u201315 (2015)","journal-title":"ICLR"},{"issue":"1","key":"61_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1326561.1326563","volume":"2","author":"L Becchetti","year":"2008","unstructured":"Becchetti, L., et al.: Link analysis for Web spam detection. ACM Trans. Web. 2(1), 1\u201342 (2008)","journal-title":"ACM Trans. Web."},{"key":"61_CR4","doi-asserted-by":"crossref","unstructured":"Chengzhang, J., Kang, D.-K.: Detecting the spam review using tri-training. In: ICACT 2015, pp. 374\u2013377 IEEE (2015)","DOI":"10.1109\/ICACT.2015.7224822"},{"key":"61_CR5","unstructured":"Faville, K., List, A.: Cone releases the 2011 online influence trend tracker. https:\/\/www.conecomm.com\/news-blog\/2011-online-influence-trend-tracker-release"},{"key":"61_CR6","unstructured":"Glorot, X., et al.: Domain adaptation for large-scale sentiment classification: a deep learning approach. In: Proceedings of the 28th International Conference on Machine Learning, ICML 2011, pp. 513\u2013520 (2011)"},{"key":"61_CR7","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"583","DOI":"10.1007\/978-3-030-32233-5_45","volume-title":"Natural Language Processing and Chinese Computing","author":"C Jiang","year":"2019","unstructured":"Jiang, C., Zhang, X.: Neural networks merging semantic and non-semantic features for opinion spam detection. In: Tang, J., Kan, M.-Y., Zhao, D., Li, S., Zan, H. (eds.) NLPCC 2019. LNCS (LNAI), vol. 11838, pp. 583\u2013595. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-32233-5_45"},{"key":"61_CR8","doi-asserted-by":"crossref","unstructured":"Jindal, N., Liu, B.: Analyzing and Detecting Review Spam. In: ICDM 2007, pp. 547\u2013552 IEEE (2007)","DOI":"10.1109\/ICDM.2007.68"},{"key":"61_CR9","unstructured":"Kolcz, A., Alspector, J.: SVM-based filtering of e-mail spam with content-specific misclassification costs. In: Proc. TextDM 2001 Workshop on Text Mining - held 2001 IEEE International Conference Data Mining, pp. 1\u20136 (2001)"},{"key":"61_CR10","unstructured":"Le, Q.V., Mikolov, T.: Distributed Representations of Sentences and Documents. In: ICML 2014 (2014)"},{"key":"61_CR11","doi-asserted-by":"crossref","unstructured":"Li, H., et al.: Spotting fake reviews via collective positive-unlabeled learning. In: 2014 IEEE International Conference on Data Mining, pp. 899\u2013904 IEEE (2014)","DOI":"10.1109\/ICDM.2014.47"},{"key":"61_CR12","doi-asserted-by":"crossref","unstructured":"Li, J., et al.: Towards a general rule for identifying deceptive opinion spam. In: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, pp. 1566\u20131576 (2014)","DOI":"10.3115\/v1\/P14-1147"},{"key":"61_CR13","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1016\/j.neucom.2016.10.080","volume":"254","author":"L Li","year":"2017","unstructured":"Li, L., et al.: Document representation and feature combination for deceptive spam review detection. Neurocomputing 254, 33\u201341 (2017)","journal-title":"Neurocomputing"},{"key":"61_CR14","doi-asserted-by":"crossref","unstructured":"Lim, E.P., et al.: Detecting product review spammers using rating behaviors. In: International Conference on Information and Knowledge Management, Proceedings, pp. 939\u2013948 (2010)","DOI":"10.1145\/1871437.1871557"},{"key":"61_CR15","first-page":"3111","volume":"2013","author":"T Mikolov","year":"2013","unstructured":"Mikolov, T., et al.: Distributed representations of words and phrases and their compositionality. NIPS 2013, 3111\u20133119 (2013)","journal-title":"NIPS"},{"key":"61_CR16","first-page":"409","volume":"2013","author":"A Mukherjee","year":"2013","unstructured":"Mukherjee, A., et al.: What yelp fake review filter might be doing? ICWSM 2013, 409\u2013418 (2013)","journal-title":"ICWSM"},{"key":"61_CR17","doi-asserted-by":"crossref","unstructured":"Ntoulas, A., et al.: Detecting spam web pages through content analysis. In: Proceedings of the 15th International Conference on World Wide Web, pp. 83\u201392 (2006)","DOI":"10.1145\/1135777.1135794"},{"key":"61_CR18","first-page":"309","volume":"2011","author":"M Ott","year":"2011","unstructured":"Ott, M., et al.: Finding deceptive opinion spam by any stretch of the imagination. ACL 2011, 309\u2013319 (2011)","journal-title":"ACL"},{"key":"61_CR19","unstructured":"Ott, M., et al.: Negative deceptive opinion spam. In: NAACL HLT 2013, pp. 497\u2013501 (2013)"},{"key":"61_CR20","unstructured":"Raffel, C., Ellis, D.P.W.: Feed-Forward Networks with Attention Can Solve Some Long- Term Memory Problems (2015)"},{"key":"61_CR21","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1016\/j.ins.2017.01.015","volume":"385\u2013386","author":"Y Ren","year":"2017","unstructured":"Ren, Y., Ji, D.: Neural networks for deceptive opinion spam detection: an empirical study. Inf. Sci. (Ny) 385\u2013386, 213\u2013224 (2017)","journal-title":"Inf. Sci. (Ny)"},{"key":"61_CR22","unstructured":"Ren, Y., Zhang, Y.: Deceptive opinion spam detection using neural network. In: COLING 2016\u201326th International Conference Computer Linguistic Proceedings COLING 2016 Technical Paper 140\u2013150 (2016)"},{"key":"61_CR23","doi-asserted-by":"crossref","unstructured":"Tang, D. et al.: document modeling with gated recurrent neural network for sentiment classification. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pp. 1422\u20131432","DOI":"10.18653\/v1\/D15-1167"},{"key":"61_CR24","unstructured":"Vaswani, A. et al.: Attention is all you need. In: Advances Neural Information Processing System 2017- Decem, Nips, 5999\u20136009 (2017)"},{"key":"61_CR25","doi-asserted-by":"crossref","unstructured":"Wang, X. et al.: Detecting Deceptive Review Spam via Attention-Based Neural Networks. In: Lecture Notes in Computer Science, pp. 866\u2013876 (2018)","DOI":"10.1007\/978-3-319-73618-1_76"},{"key":"61_CR26","doi-asserted-by":"crossref","unstructured":"Wang, X. et al.: Identification of fake reviews using semantic and behavioral features. In: 2018 4th International Conference on Information Management, ICIM 2018, pp. 92\u201397 Springer (2018)","DOI":"10.1109\/INFOMAN.2018.8392816"},{"key":"61_CR27","doi-asserted-by":"crossref","unstructured":"Xu, W., Rudnicky, A.: Can artificial neural networks learn language models? In: 6th International Conference on Spoken Language Processing, ICSLP 2000 (2000)","DOI":"10.21437\/ICSLP.2000-50"},{"key":"61_CR28","first-page":"37","volume":"2009","author":"K-H Yoo","year":"2009","unstructured":"Yoo, K.-H., Gretzel, U.: Comparison of deceptive and truthful travel reviews. Inf. Commun. Technol. Tourism 2009, 37\u201347 (2009)","journal-title":"Inf. Commun. Technol. Tourism"}],"container-title":["Lecture Notes in Computer Science","Neural Information Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-63830-6_61","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T13:58:19Z","timestamp":1709819899000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-63830-6_61"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030638290","9783030638306"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-63830-6_61","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"19 November 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICONIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Neural Information Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bangkok","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Thailand","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 November 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 November 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iconip2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.apnns.org\/ICONIP2020","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"618","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"187","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"189","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"30% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.18","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.68","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Due to COVID-19 pandemic the conference was held virtually.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}