{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,10]],"date-time":"2024-09-10T20:16:42Z","timestamp":1725999402101},"publisher-location":"Cham","reference-count":26,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030010560"},{"type":"electronic","value":"9783030010577"}],"license":[{"start":{"date-parts":[[2018,11,8]],"date-time":"2018-11-08T00:00:00Z","timestamp":1541635200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-01057-7_58","type":"book-chapter","created":{"date-parts":[[2018,11,7]],"date-time":"2018-11-07T15:45:17Z","timestamp":1541605517000},"page":"773-787","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Temporal Spam Identification: A Multifaceted Approach to Identifying Review Spam"],"prefix":"10.1007","author":[{"given":"Iqra","family":"Muhammad","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Usman","family":"Qamar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Farhan Hassan","family":"Khan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,11,8]]},"reference":[{"key":"58_CR1","unstructured":"Ott, M., Choi, Y., Cardie, C., Hancock, J.T.: Finding deceptive opinion spam by any stretch of the imagination. Presented at the proceedings of the 49th annual meeting of the association for computational linguistics: human language technologies, vol. 1, Portland, Oregon (2011)"},{"key":"58_CR2","unstructured":"Li, H., Chen, Z., Mukherjee, A., Liu, B., Shao, J.: Analyzing and detecting opinion spam on a large-scale dataset via temporal and spatial patterns (2015)"},{"key":"58_CR3","unstructured":"Li, H., Fei, G., Wang, S., Liu, B., Shao, W., Mukherjee, A., et al.: Modeling Review Spam Using Temporal Patterns and Co-bursting Behaviors. arXiv preprint arXiv:1611.06625 (2016)"},{"key":"58_CR4","doi-asserted-by":"crossref","unstructured":"Jindal, N., Liu, B.: Opinion spam and analysis. In: Proceedings of the 2008 International Conference on Web Search and Data Mining, pp. 219\u2013230 (2008)","DOI":"10.1145\/1341531.1341560"},{"key":"58_CR5","doi-asserted-by":"crossref","unstructured":"Li, J., Ott, M., Cardie, C., Hovy, E.: Towards a general rule for identifying deceptive opinion spam. In: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 1566\u20131576 (2014)","DOI":"10.3115\/v1\/P14-1147"},{"key":"58_CR6","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1007\/978-3-319-18117-2_21","volume-title":"Computational Linguistics and Intelligent Text Processing","author":"Donato Hern\u00e1ndez Fusilier","year":"2015","unstructured":"Fusilier, D.H., Montes-y-G\u00f3mez, M., Rosso, P., Cabrera, R.G.: Detection of opinion spam with character n-grams. In: International Conference on Intelligent Text Processing and Computational Linguistics, pp. 285\u2013294 (2015)"},{"key":"58_CR7","doi-asserted-by":"publisher","first-page":"433","DOI":"10.1016\/j.ipm.2014.11.001","volume":"51","author":"DH Fusilier","year":"2015","unstructured":"Fusilier, D.H., Montes-y-G\u00f3mez, M., Rosso, P., Cabrera, R.G.: Detecting positive and negative deceptive opinions using PU-learning. Inf. Process. Manage. 51, 433\u2013443 (2015)","journal-title":"Inf. Process. Manage."},{"key":"58_CR8","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1016\/j.eswa.2016.03.020","volume":"58","author":"A Heydari","year":"2016","unstructured":"Heydari, A., Tavakoli, M., Salim, N.: Detection of fake opinions using time series. Expert Syst. Appl. 58, 83\u201392 (2016)","journal-title":"Expert Syst. Appl."},{"key":"58_CR9","doi-asserted-by":"crossref","unstructured":"Crawford, M., Khoshgoftaar, T.M., Prusa, J.D., Richter, A.N., Al Najada, H.: Survey of review spam detection using machine-learning techniques. J. Big Data 2, 23 (2015)","DOI":"10.1186\/s40537-015-0029-9"},{"issue":"4","key":"58_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2070710.2070716","volume":"2","author":"Raymond Y. K. Lau","year":"2011","unstructured":"Lau, R.Y., Liao, S., Kwok, R.C.-W., Xu, K., Xia, Y., Li, Y.: Text mining and probabilistic language modeling for online review spam detection. ACM Trans. Manage. Inf. Syst. (TMIS) 2, 25 (2011)","journal-title":"ACM Transactions on Management Information Systems"},{"key":"58_CR11","doi-asserted-by":"crossref","unstructured":"Mukherjee, A., Liu, B., Glance, N.: Spotting fake reviewer groups in consumer reviews. In: Proceedings of the 21st International Conference on World Wide Web, pp. 191\u2013200 (2012)","DOI":"10.1145\/2187836.2187863"},{"key":"58_CR12","doi-asserted-by":"crossref","unstructured":"Jindal, N., Liu, B., Lim, E.-P.: Finding unusual review patterns using unexpected rules. In: Proceedings of the 19th ACM International Conference on Information and Knowledge Management, pp. 1549\u20131552 (2010)","DOI":"10.1145\/1871437.1871669"},{"key":"58_CR13","unstructured":"Mukherjee, A., Venkataraman, V., Liu, B., Glance, N.S.: What Yelp fake review filter might be doing? In: ICWSM (2013)"},{"key":"58_CR14","doi-asserted-by":"crossref","unstructured":"Almeida, T.A., Hidalgo, J.M.G., Yamakami, A.: Contributions to the study of SMS spam-filtering: new collection and results. In: Proceedings of the 11th ACM Symposium on Document Engineering, pp. 259\u2013262 (2011)","DOI":"10.1145\/2034691.2034742"},{"key":"58_CR15","doi-asserted-by":"crossref","unstructured":"Dewang, R.K., Singh, P., Singh, A.K.: Finding of review spam through Corleone, review genre, writing style and review text detail features. In: Proceedings of the Second International Conference on Information and Communication Technology for Competitive Strategies, p. 23 (2016)","DOI":"10.1145\/2905055.2905081"},{"key":"58_CR16","doi-asserted-by":"crossref","unstructured":"Mukherjee, A., Kumar, A., Liu, B., Wang, J., Hsu, M. Castellanos, M., et al.: Spotting opinion spammers using behavioral footprints. In: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 632\u2013640 (2013)","DOI":"10.1145\/2487575.2487580"},{"key":"58_CR17","doi-asserted-by":"crossref","unstructured":"Bakhshi, S., Kanuparthy, P., Shamma, D.A.: Understanding online reviews: funny, cool or useful? In: Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing, pp. 1270\u20131276 (2015)","DOI":"10.1145\/2675133.2675275"},{"key":"58_CR18","doi-asserted-by":"crossref","unstructured":"Kc, S., Mukherjee, A.: On the temporal dynamics of opinion spamming. In: Proceedings of the 25th International Conference on World Wide Web\u2014WWW 16 (2016)","DOI":"10.1145\/2872427.2883087"},{"key":"58_CR19","unstructured":"Mukherjee, A., Venkataraman, V., Liu, B., Glance, N.: Fake review detection: classification and analysis of real and pseudo reviews. Technical Report UIC-CS-2013\u201303, University of Illinois at Chicago, Technical Report (2013)"},{"key":"58_CR20","unstructured":"Yelp: Yelp, 2017. [Online]. Available: http:\/\/www.Yelp.com . Accessed 06 Dec 2017"},{"key":"58_CR21","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Zhang, H., Zhang, M., Liu, Y., Ma, S.: Do users rate or review?: boost phrase-level sentiment labeling with review-level sentiment classification. In: Proceedings of the 37th International ACM SIGIR Conference on Research & Development in Information Retrieval, pp. 1027\u20131030 (2014)","DOI":"10.1145\/2600428.2609501"},{"key":"58_CR22","unstructured":"PeakUtils 1.1.0: Python Package Index. [Online]. Available: https:\/\/pypi.python.org\/pypi\/PeakUtils . Accessed 07 Dec 2017"},{"key":"58_CR23","unstructured":"Natural Language Toolkit: Natural Language Toolkit\u2014NLTK 3.2.5 documentation. [Online]. Available: http:\/\/www.nltk.org\/ . Accessed 07 Dec 2017"},{"key":"58_CR24","unstructured":"Scikit-learn: Scikit-learn: machine-learning in Python\u2014scikit-learn 0.19.1 documentation. [Online]. Available: http:\/\/scikit-learn.org\/stable\/ . Accessed 07 Dec 2017"},{"key":"58_CR25","doi-asserted-by":"crossref","unstructured":"Fei, G., Mukherjee, A., Liu, B., Hsu, M., Castellanos, M., Ghosh, R.: Exploiting burstiness in reviews for review spammer detection. In: Icwsm, vol. 13, pp. 175\u2013184 (2013)","DOI":"10.1609\/icwsm.v7i1.14400"},{"key":"58_CR26","first-page":"581","volume-title":"SOFSEM 2018: Theory and Practice of Computer Science","author":"Ioannis Dematis","year":"2017","unstructured":"Dematis, I., Karapistoli, E., Vakali, A.: Fake review detection via exploitation of spam indicators and reviewer behavior characteristics. In: International Conference on Current Trends in Theory and Practice of Informatics, pp. 581\u2013595 (2018)"}],"container-title":["Advances in Intelligent Systems and Computing","Intelligent Systems and Applications"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-01057-7_58","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,6]],"date-time":"2023-09-06T17:45:40Z","timestamp":1694022340000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-01057-7_58"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,11,8]]},"ISBN":["9783030010560","9783030010577"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-01057-7_58","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2018,11,8]]},"assertion":[{"value":"IntelliSys","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Proceedings of SAI Intelligent Systems Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"London","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"intellisys2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/saiconference.com\/IntelliSys2018\/CallforPapers","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}