{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T17:52:56Z","timestamp":1783619576032,"version":"3.55.0"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030198091","type":"print"},{"value":"9783030198107","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"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\/978-3-030-19810-7_30","type":"book-chapter","created":{"date-parts":[[2019,5,6]],"date-time":"2019-05-06T14:01:20Z","timestamp":1557151280000},"page":"307-315","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Bot Detection on Online Social Networks Using Deep Forest"],"prefix":"10.1007","author":[{"given":"Kheir Eddine","family":"Daouadi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rim Zghal","family":"Reba\u00ef","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ikram","family":"Amous","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2019,5,5]]},"reference":[{"key":"30_CR1","doi-asserted-by":"crossref","unstructured":"Subrahmanian, V.S., Azaria, A., Durst, S., Kagan, V., Galstyan, A., Lerman, K., Stevens, A.: The DARPA Twitter bot challenge.\u00a0arXiv preprint arXiv:1601.05140 (2016)","DOI":"10.1109\/MC.2016.183"},{"key":"30_CR2","doi-asserted-by":"crossref","unstructured":"Varol, O., Ferrara, E., Davis, C., Menczer, F., Flammini, A.: Online human-bot interactions: detection, estimation, and characterization. In: 11th International AAAI Conference on Web and Social Media, pp. 1\u201310. AAAI, Canada (2017)","DOI":"10.1609\/icwsm.v11i1.14871"},{"key":"30_CR3","doi-asserted-by":"crossref","unstructured":"Kantepe, M., Ganiz, M.C.: Preprocessing framework for Twitter bot detection. In:\u00a0Computer Science and Engineering (UBMK), pp. 630\u2013634. IEEE, Turkey (2017)","DOI":"10.1109\/UBMK.2017.8093483"},{"key":"30_CR4","unstructured":"Pozzana, I., Ferrara, E.: Measuring bot and human behavioral dynamics.\u00a0arXiv preprint arXiv:1802.04286 (2018)"},{"key":"30_CR5","doi-asserted-by":"crossref","unstructured":"Chavoshi, N., Hamooni, H., Mueen, A.: On-demand bot detection and archival system. In:\u00a0Proceedings of the 26th International Conference on World Wide Web Companion, pp. 183\u2013187. ACM, Australia (2017)","DOI":"10.1145\/3041021.3054733"},{"key":"30_CR6","doi-asserted-by":"crossref","unstructured":"Cai, C., Li, L., Zengi, D.: Behavior enhanced deep bot detection in social media. In: International Conference on Intelligence and Security Informatics (ISI), pp. 128\u2013130. IEEE, China (2017)","DOI":"10.1109\/ISI.2017.8004887"},{"key":"30_CR7","doi-asserted-by":"crossref","unstructured":"Ferrara, E.: Disinformation and social bot operations in the run up to the 2017 French presidential election.\u00a0First Monday, 22(8) (2017)","DOI":"10.5210\/fm.v22i8.8005"},{"key":"30_CR8","doi-asserted-by":"publisher","first-page":"10805","DOI":"10.1109\/ACCESS.2017.2706674","volume":"5","author":"RG Guimaraes","year":"2017","unstructured":"Guimaraes, R.G., Rosa, R.L., De Gaetano, D., Rodriguez, D.Z., Bressan, G.: Age groups classification in social network using deep learning. IEEE Access 5, 10805\u201310816 (2017)","journal-title":"IEEE Access"},{"key":"30_CR9","doi-asserted-by":"crossref","unstructured":"Kim, S.M., Paris, C., Power, R., Wan, S.: Distinguishing individuals from organisations on Twitter. In: Proceedings of the 26th International Conference on World Wide Web Companion, pp. 805\u2013806. ACM, Australia (2017)","DOI":"10.1145\/3041021.3054217"},{"issue":"7","key":"30_CR10","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1145\/2818717","volume":"59","author":"E Ferrara","year":"2016","unstructured":"Ferrara, E., Varol, O., Davis, C., Menczer, F., Flammini, A.: The rise of social bots. Commun. ACM 59(7), 96\u2013104 (2016)","journal-title":"Commun. ACM"},{"issue":"19","key":"30_CR11","doi-asserted-by":"publisher","first-page":"e4209","DOI":"10.1002\/cpe.4209","volume":"29","author":"T Wu","year":"2017","unstructured":"Wu, T., Wen, S., Liu, S., Zhang, J., Xiang, Y., Alrubaian, M., Hassan, M.M.: Detecting spamming activities in twitter based on deep-learning technique. Concurr. Comput. : Pract. Exp. 29(19), e4209 (2017)","journal-title":"Concurr. Comput. : Pract. Exp."},{"issue":"4","key":"30_CR12","first-page":"561","volume":"15","author":"S Cresci","year":"2018","unstructured":"Cresci, S., Di Pietro, R., Petrocchi, M., Spognardi, A., Tesconi, M.: Social fingerprinting: detection of spambot groups through DNA-inspired behavioral modeling. IEEE Trans. Dependable Secure Comput. 15(4), 561\u2013576 (2018)","journal-title":"IEEE Trans. Dependable Secure Comput."},{"key":"30_CR13","doi-asserted-by":"crossref","unstructured":"Morstatter, F., Wu, L., Nazer, T.H., Carley, K.M., Liu, H.: A new approach to bot detection: striking the balance between precision and recall. In: Proceedings of the 2016 IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 533\u2013540. IEEE Press, USA (2016)","DOI":"10.1109\/ASONAM.2016.7752287"},{"key":"30_CR14","doi-asserted-by":"crossref","unstructured":"Gilani, Z., Kochmar, E., Crowcroft, J.: Classification of twitter accounts into automated agents and human users. In: Proceedings of the 2017 IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 489\u2013496. ACM, Australia (2017)","DOI":"10.1145\/3110025.3110091"},{"key":"30_CR15","doi-asserted-by":"crossref","unstructured":"Bindu, P.V., Mishra, R., Thilagam, P.S.: Discovering spammer communities in Twitter.\u00a0J. Intell. Inf. Syst., 1\u201325 (2018)","DOI":"10.1007\/s10844-017-0494-z"},{"key":"30_CR16","first-page":"970","volume":"86057","author":"GM Tavares","year":"2017","unstructured":"Tavares, G.M., Mastelini, S.M., Barbon Jr., S.: User classification on online social networks by post frequency. CEP 86057, 970 (2017)","journal-title":"CEP"},{"key":"30_CR17","doi-asserted-by":"crossref","unstructured":"Lee, K., Eoff, B.D., Caverlee, J.: Seven months with the devils: a long-term study of content polluters on Twitter. In: ICWSM, pp. 185\u2013192 (2011)","DOI":"10.1609\/icwsm.v5i1.14106"},{"key":"30_CR18","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1613\/jair.953","volume":"16","author":"NV Chawla","year":"2002","unstructured":"Chawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, W.P.: SMOTE: synthetic minority over-sampling technique. J. Artif. Intell. Res. 16, 321\u2013357 (2002)","journal-title":"J. Artif. Intell. Res."},{"key":"30_CR19","doi-asserted-by":"crossref","unstructured":"Zhou, Z.H., Feng, J.: Deep forest: towards an alternative to deep neural networks.\u00a0arXiv preprint arXiv:1702.08835 (2017)","DOI":"10.24963\/ijcai.2017\/497"}],"container-title":["Advances in Intelligent Systems and Computing","Artificial Intelligence Methods in Intelligent Algorithms"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-19810-7_30","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,16]],"date-time":"2023-09-16T08:26:55Z","timestamp":1694852815000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-19810-7_30"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030198091","9783030198107"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-19810-7_30","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"value":"2194-5357","type":"print"},{"value":"2194-5365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"5 May 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CSOC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Computer Science On-line Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Zlin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Czech Republic","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 April 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 April 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"csolc2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/csoc.openpublish.eu","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}