{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T07:40:22Z","timestamp":1782286822207,"version":"3.54.5"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2021,4,20]],"date-time":"2021-04-20T00:00:00Z","timestamp":1618876800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2021,4,20]],"date-time":"2021-04-20T00:00:00Z","timestamp":1618876800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2023,1]]},"DOI":"10.1007\/s00521-021-05948-1","type":"journal-article","created":{"date-parts":[[2021,4,20]],"date-time":"2021-04-20T12:02:34Z","timestamp":1618920154000},"page":"1169-1182","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Fake review and reviewer detection through behavioral graph partitioning integrating deep neural network"],"prefix":"10.1007","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8075-2787","authenticated-orcid":false,"given":"Bundit","family":"Manaskasemsak","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jirateep","family":"Tantisuwankul","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7960-790X","authenticated-orcid":false,"given":"Arnon","family":"Rungsawang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,4,20]]},"reference":[{"key":"5948_CR1","doi-asserted-by":"crossref","unstructured":"Akoglu L, Chandy R, Faloutsos C (2013) Opinion fraud detection in online reviews by network effects. In: Proceedings of the 7th International AAAI Conference on Weblogs and Social Media","DOI":"10.1609\/icwsm.v7i1.14380"},{"key":"5948_CR2","unstructured":"Baccianella S, Esuli A, Sebastiani F (2010) Sentiwordnet 3.0: An enhanced lexical resource for sentiment analysis and opinion mining. In: Proceedings of the 7th International Conference on Language Resources and Evaluation, 10, 2200\u20132204"},{"issue":"10","key":"5948_CR3","doi-asserted-by":"publisher","first-page":"3538","DOI":"10.1007\/s10489-018-1161-y","volume":"48","author":"A Barushka","year":"2018","unstructured":"Barushka A, Hajek P (2018) Spam filtering using integrated distribution-based balancing approach and regularized deep neural networks. Appl Intell 48(10):3538\u20133556","journal-title":"Appl Intell"},{"key":"5948_CR4","doi-asserted-by":"publisher","first-page":"340","DOI":"10.1007\/978-3-030-19823-7_28","volume-title":"15th IFIP International Conference on Artificial Intelligence Applications and Innovations","author":"A Barushka","year":"2019","unstructured":"Barushka A, Hajek P (2019) Review spam detection using word embeddings and deep neural networks. In: MacIntyre J, Maglogiannis I, Iliadis L, Pimenidis E (eds) 15th IFIP International Conference on Artificial Intelligence Applications and Innovations, vol 559. Springer, Cham, pp 340\u2013350"},{"key":"5948_CR5","unstructured":"Bergstra J, Bardenet R, Bengio Y, K\u00e9gl B (2011) Algorithms for hyper-parameter optimization. In: Shawe-Taylor J, Zemel R, Bartlett P, Pereira F, Weinberger K (eds) 25th International Conference on Neural Information Processing Systems, vol 24, Neural Information Processing Systems Foundation, pp 2546\u20132554"},{"key":"5948_CR6","unstructured":"Bergstra J, Yamins D, Cox D (2013) Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vision architectures. In: Proceedings of the 30th International Conference on Machine Learning, 28, 115\u2013123"},{"key":"5948_CR7","doi-asserted-by":"crossref","unstructured":"Blum A, Mitchell T (1998) Combining labeled and unlabeled data with co-training. In: Proceedings of the 11th Annual Conference on Computational Learning Theory, pp. 92\u2013100","DOI":"10.1145\/279943.279962"},{"key":"5948_CR8","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1016\/j.knosys.2014.05.016","volume":"69","author":"F Bravo-Marquez","year":"2014","unstructured":"Bravo-Marquez F, Mendoza M, Poblete B (2014) Meta-level sentiment models for big social data analysis. Knowl-Based Syst 69:86\u201399","journal-title":"Knowl-Based Syst"},{"issue":"4","key":"5948_CR9","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1109\/MIC.2015.28","volume":"19","author":"D Chatzakou","year":"2015","unstructured":"Chatzakou D, Vakali A (2015) Harvesting opinions and emotions from social media textual resources. IEEE Internet Comput 19(4):46\u201350","journal-title":"IEEE Internet Comput"},{"key":"5948_CR10","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1186\/s40537-015-0029-9","volume":"2","author":"M Crawford","year":"2015","unstructured":"Crawford M, Khoshgoftaar TM, Prusa JD, Richter AN, Najada HA (2015) Survey of review spam detection using machine learning techniques. J Big Data 2:23","journal-title":"J Big Data"},{"key":"5948_CR11","doi-asserted-by":"crossref","unstructured":"Fei G, Mukherjee A, Liu B, Hsu M, Castellanos M, Ghosh R (2013) Exploiting burstiness in reviews for review spammer detection. In: Proceedings of the 7th International AAAI Conference on Weblogs and Social Media, pp. 175\u2013184","DOI":"10.1609\/icwsm.v7i1.14400"},{"key":"5948_CR12","doi-asserted-by":"crossref","unstructured":"Feng S, Xing L, Gogar A, Choi Y (2012) Distributional footprints of deceptive product reviews. In: Proceedings of the 6th International AAAI Conference on Weblogs and Social Media, pp. 98\u2013105","DOI":"10.1609\/icwsm.v6i1.14275"},{"key":"5948_CR13","unstructured":"Fusilier DH, Cabrera RG, Montes-y-G\u00f3mez M, Rosso P (2013) Using pu-learning to detect deceptive opinion spam. In: Proceedings of the 4th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, pp. 38\u201345"},{"issue":"23","key":"5948_CR14","doi-asserted-by":"publisher","first-page":"17259","DOI":"10.1007\/s00521-020-04757-2","volume":"32","author":"P Hajek","year":"2020","unstructured":"Hajek P, Barushka A, Munk M (2020) Fake consumer review detection using deep neural networks integrating word embeddings and emotion mining. Neural Comput Appl 32(23):17259\u201317274","journal-title":"Neural Comput Appl"},{"key":"5948_CR15","unstructured":"Heaton J (2008) Introduction to Neural Networks for Java, 2nd edn., chap. 5. Feedforward Neural Networks. Heaton Research, Inc"},{"key":"5948_CR16","doi-asserted-by":"crossref","unstructured":"Hu M, Liu B (2004) Mining and summarizing customer reviews. In: Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 168\u2013177","DOI":"10.1145\/1014052.1014073"},{"issue":"5","key":"5948_CR17","doi-asserted-by":"publisher","first-page":"987","DOI":"10.3390\/app9050987","volume":"9","author":"N Hussain","year":"2019","unstructured":"Hussain N, Mirza HT, Rasool G, Hussain I, Kaleem M (2019) Spam review detection techniques: A systematic literature review. Appl Sci 9(5):987","journal-title":"Appl Sci"},{"key":"5948_CR18","doi-asserted-by":"crossref","unstructured":"Jindal N, Liu B (2007) Analyzing and detecting review spam. In: Proceedings of the 7th IEEE International Conference on Data Mining, pp. 547\u2013552","DOI":"10.1109\/ICDM.2007.68"},{"key":"5948_CR19","doi-asserted-by":"crossref","unstructured":"Jindal N, Liu B (2008) Opinion spam and analysis. In: Proceedings of the International Conference on Web Search and Data Mining, pp. 219\u2013230","DOI":"10.1145\/1341531.1341560"},{"key":"5948_CR20","doi-asserted-by":"crossref","unstructured":"Jindal N, Liu B, Lim EP (2010) Finding unusual review patterns using unexpected rules. In: Proceedings of the 19th ACM International Conference on Information and Knowledge Management, pp. 1549\u20131552","DOI":"10.1145\/1871437.1871669"},{"issue":"1","key":"5948_CR21","doi-asserted-by":"publisher","first-page":"723","DOI":"10.1613\/jair.4272","volume":"50","author":"S Kiritchenko","year":"2014","unstructured":"Kiritchenko S, Zhu X, Mohammad SM (2014) Sentiment analysis of short informal texts. J Artif Intell Res 50(1):723\u2013762","journal-title":"J Artif Intell Res"},{"key":"5948_CR22","doi-asserted-by":"crossref","unstructured":"Koven J, Siadati H, Lin CY (2014) Finding valuable yelp comments by personality, content, geo, and anomaly analysis. In: Proceedings of the 2014 IEEE International Conference on Data Mining Workshop, pp. 1215\u20131218","DOI":"10.1109\/ICDMW.2014.49"},{"key":"5948_CR23","doi-asserted-by":"crossref","unstructured":"Lak P, Turetken O (2014) Star ratings versus sentiment analysis \u2013 a comparison of explicit and implicit measures of opinions. In: Proceedings of 47th Hawaii International Conference on System Sciences, pp. 796\u2013805","DOI":"10.1109\/HICSS.2014.106"},{"key":"5948_CR24","unstructured":"Le Q, Mikolov T (2014) Distributed representations of sentences and documents. In: Proceedings of the 31st International Conference on Machine Learning, pp. 1188\u20131196"},{"key":"5948_CR25","unstructured":"Li F, Huang M, Yang Y, Zhu X (2011) Learning to identify review spam. In: Proceedings of the 22nd International Joint Conference on Artificial Intelligence, pp. 2488\u20132493"},{"key":"5948_CR26","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, Qin B, Ren W, Liu T (2017) Document representation and feature combination for deceptive spam review detection. Neurocomputing 254:33\u201341","journal-title":"Neurocomputing"},{"key":"5948_CR27","doi-asserted-by":"crossref","unstructured":"Lim EP, Nguyen VA, Jindal N, Liu B, Lauw HW (2010) Detecting product review spammers using rating behaviors. In: Proceedings of the 19th ACM International Conference on Information and Knowledge Management, pp. 939\u2013948","DOI":"10.1145\/1871437.1871557"},{"key":"5948_CR28","doi-asserted-by":"crossref","unstructured":"Liu B, Dai Y, Li X, Lee WS, Yu PS (2003) Building text classifiers using positive and unlabeled examples. In: Proceedings of the 3rd IEEE International Conference on Data Mining, pp. 179\u2013186","DOI":"10.1109\/ICDM.2003.1250918"},{"key":"5948_CR29","unstructured":"Liu J, Cao Y, Lin CY, Huang Y, Zhou M (2007) Low-quality product review detection in opinion summarization. In: Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, pp. 334\u2013342"},{"key":"5948_CR30","doi-asserted-by":"crossref","unstructured":"Manaskasemsak B, Chanmakho C, Klainongsuang J, Rungsawang A (2019) Opinion spam detection through user behavioral graph partitioning approach. In: Proceedings of the 3rd International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence, pp. 73\u201377","DOI":"10.1145\/3325773.3325783"},{"key":"5948_CR31","unstructured":"Mikolov T, Sutskever I, Chen K, Corrado G, Dean J (2013) Distributed representations of words and phrases and their compositionality. In: Proceedings of the 26th International Conference on Neural Information Processing Systems, pp. 3111\u20133119"},{"key":"5948_CR32","unstructured":"Mohammad SM, Kiritchenko S, Zhu X (2013) NRC-Canada: Building the state-of-the-art in sentiment analysis of tweets. In: Proceedings of the 2nd Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the 7th International Workshop on Semantic Evaluation (SemEval 2013)"},{"key":"5948_CR33","unstructured":"Mohammad SM, Turney PD (2010) Emotions evoked by common words and phrases: Using mechanical turk to create an emotion lexicon. In: Proceedings of the NAACL-HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text, pp. 26\u201334"},{"issue":"3","key":"5948_CR34","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1111\/j.1467-8640.2012.00460.x","volume":"29","author":"SM Mohammad","year":"2013","unstructured":"Mohammad SM, Turney PD (2013) Crowdsourcing a word-emotion association lexicon. Comput Intell 29(3):436\u2013465","journal-title":"Comput Intell"},{"key":"5948_CR35","doi-asserted-by":"crossref","unstructured":"Mukherjee A, Kumar A, Liu B, Wang J, Hsu M, Castellanos M, Ghosh R (2013) Spotting opinion spammers using behavioral footprints. In: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 632\u2013640","DOI":"10.1145\/2487575.2487580"},{"key":"5948_CR36","doi-asserted-by":"crossref","unstructured":"Mukherjee A, Venkataraman V, Liu B, Glance N (2013) What yelp fake review filter might be doing? In: Proceedings of the 7th International AAAI Conference on Weblogs and Social Media, pp. 409\u2013418","DOI":"10.1609\/icwsm.v7i1.14389"},{"key":"5948_CR37","unstructured":"Murphy R (2019) Local consumer review survey. https:\/\/www.brightlocal.com\/research\/local-consumer-review-survey\/. Accessed: 20 April 2020"},{"key":"5948_CR38","unstructured":"Nielsen F\u00c5 (2011) A new ANEW: Evaluation of a word list for sentiment analysis in microblogs. In: Proceedings of the ESWC2011 Workshop on \u2018Making Sense of Microposts\u2019: Big things come in small packages, pp. 93\u201398"},{"issue":"8","key":"5948_CR39","doi-asserted-by":"publisher","first-page":"2065","DOI":"10.4304\/jsw.9.8.2065-2072","volume":"9","author":"Q Peng","year":"2014","unstructured":"Peng Q, Zhong M (2014) Detecting spam review through sentiment analysis. J Softw 9(8):2065\u20132072","journal-title":"J Softw"},{"key":"5948_CR40","first-page":"1","volume-title":"Emot Psychopathol","author":"R Plutchik","year":"1988","unstructured":"Plutchik R (1988) The nature of emotions: clinical implications. In: Clynes M, Panksepp J (eds) Emot Psychopathol. Springer, Boston, MA, pp 1\u201320"},{"key":"5948_CR41","doi-asserted-by":"crossref","unstructured":"Rayana S, Akoglu L (2015) Collective opinion spam detection: Bridging review networks and metadata. In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 985\u2013994","DOI":"10.1145\/2783258.2783370"},{"key":"5948_CR42","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 (2017) Neural networks for deceptive opinion spam detection: An empirical study. Inf Sci 385\u2013386:213\u2013224","journal-title":"Inf Sci"},{"issue":"5","key":"5948_CR43","doi-asserted-by":"publisher","first-page":"513","DOI":"10.1016\/0306-4573(88)90021-0","volume":"24","author":"G Salton","year":"1998","unstructured":"Salton G, Buckley C (1998) Term-weighting approaches in automatic text retrieval. Inf Process Manage 24(5):513\u2013523","journal-title":"Inf Process Manage"},{"key":"5948_CR44","doi-asserted-by":"crossref","unstructured":"Sharma K, Lin KI (2013) Review spam detector with rating consistency check. In: Proceedings of the 51st ACM Southeast Conference, 24, 1\u20136","DOI":"10.1145\/2498328.2500083"},{"key":"5948_CR45","doi-asserted-by":"crossref","unstructured":"Tan E, Guo L, Chen S, Zhang X, Zhao Y (2013) Unik: Unsupervised social network spam detection. In: Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, pp. 479\u2013488","DOI":"10.1145\/2505515.2505581"},{"key":"5948_CR46","doi-asserted-by":"crossref","unstructured":"Wang G, Xie S, Liu B, Yu PS (2011) Review graph based online store review spammer detection. In: Proceedings of the 11th IEEE International Conference on Data Mining, pp. 1242\u20131247","DOI":"10.1109\/ICDM.2011.124"},{"key":"5948_CR47","doi-asserted-by":"publisher","first-page":"1621","DOI":"10.1007\/s10618-020-00693-w","volume":"34","author":"Z Wang","year":"2020","unstructured":"Wang Z, Hu R, Chen Q, Gao P, Xu X (2020) Collueagle: Collusive review spammer detection using markov random fields. Data Min Knowl Disc 34:1621\u20131641","journal-title":"Data Min Knowl Disc"},{"key":"5948_CR48","doi-asserted-by":"crossref","unstructured":"Wilson T, Wiebe J, Hoffmann P (2005) Recognizing contextual polarity in phrase-level sentiment analysis. In: Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing, pp. 347\u2013354","DOI":"10.3115\/1220575.1220619"},{"key":"5948_CR49","doi-asserted-by":"crossref","unstructured":"Xie S, Wang G, Lin S, Yu PS (2012) Review spam detection via temporal pattern discovery. In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 823\u2013831","DOI":"10.1145\/2339530.2339662"},{"key":"5948_CR50","doi-asserted-by":"crossref","unstructured":"Zhu X, Kiritchenko S, Mohammad SM (2014) NRC-Canada-2014: Recent improvements in the sentiment analysis of tweets. In: Proceedings of the 8th International Workshop on Semantic Evaluation, pp. 443\u2013447","DOI":"10.3115\/v1\/S14-2077"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-021-05948-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-021-05948-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-021-05948-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,9]],"date-time":"2023-01-09T17:10:11Z","timestamp":1673284211000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-021-05948-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,20]]},"references-count":50,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2023,1]]}},"alternative-id":["5948"],"URL":"https:\/\/doi.org\/10.1007\/s00521-021-05948-1","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,4,20]]},"assertion":[{"value":"3 May 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 March 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 April 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}