{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T18:53:12Z","timestamp":1742928792860,"version":"3.40.3"},"publisher-location":"Cham","reference-count":32,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030815226"},{"type":"electronic","value":"9783030815233"}],"license":[{"start":{"date-parts":[[2021,8,18]],"date-time":"2021-08-18T00:00:00Z","timestamp":1629244800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,8,18]],"date-time":"2021-08-18T00:00:00Z","timestamp":1629244800000},"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":[[2022]]},"DOI":"10.1007\/978-3-030-81523-3_21","type":"book-chapter","created":{"date-parts":[[2021,8,17]],"date-time":"2021-08-17T17:12:29Z","timestamp":1629220349000},"page":"210-218","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Using Machine Learning to Detect the\u00a0Signs of Radicalization and Hate Speech on Twitter"],"prefix":"10.1007","author":[{"given":"Marcin","family":"Kuchczy\u0144ski","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aleksandra","family":"Pawlicka","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marek","family":"Pawlicki","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Micha\u0142","family":"Chora\u015b","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,8,18]]},"reference":[{"issue":"23","key":"21_CR1","doi-asserted-by":"publisher","first-page":"8614","DOI":"10.3390\/app10238614","volume":"10","author":"R Alshalan","year":"2020","unstructured":"Alshalan, R., Al-Khalifa, H.: A deep learning approach for automatic hate speech detection in the Saudi Twittersphere. Appl. Sci. 10(23), 8614 (2020). https:\/\/doi.org\/10.3390\/app10238614","journal-title":"Appl. Sci."},{"key":"21_CR2","unstructured":"Article 19: UN HRC maintains consensus on Internet resolution (2018). https:\/\/tinyurl.com\/tp3p7pu3"},{"key":"21_CR3","first-page":"1137","volume":"3","author":"Y Bengio","year":"2003","unstructured":"Bengio, Y., Ducharme, R., Vincent, P., Jauvin, C.: A neural probabilistic language model. J. Mach. Learn. Res. 3, 1137\u20131155 (2003)","journal-title":"J. Mach. Learn. Res."},{"key":"21_CR4","unstructured":"Berger, J., Morgan, J.: The ISIS Twitter census defining and describing the population of ISIS supporters on Twitter. Technical report, The Brookings Project on U.S. Relations with the Islamic World, Washington (2015)"},{"issue":"1","key":"21_CR5","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1080\/17524032.2018.1527378","volume":"13","author":"EF Bloomfield","year":"2019","unstructured":"Bloomfield, E.F., Tillery, D.: The circulation of climate change denial online: rhetorical and networking strategies on Facebook. Environ. Commun. 13(1), 23\u201334 (2019). https:\/\/doi.org\/10.1080\/17524032.2018.1527378","journal-title":"Environ. Commun."},{"key":"21_CR6","unstructured":"Bobriakov, I.: Sentiment analysis with naive bayes and LSTM. Data Science Central (2020). https:\/\/tinyurl.com\/5mdzkf4h"},{"key":"21_CR7","unstructured":"Bradshaw, S., Howard, P.N.: The global disinformation order 2019 global inventory of organised social media manipulation. Technical report, Computational Propaganda Research Project (2019). https:\/\/tinyurl.com\/mz9nf5j8"},{"key":"21_CR8","doi-asserted-by":"crossref","unstructured":"Chora\u015b, M., et al.: Advanced machine learning techniques for fake news (online disinformation) detection: a systematic mapping study. Appl. Soft Comput. 101, 107050 (2020)","DOI":"10.1016\/j.asoc.2020.107050"},{"key":"21_CR9","doi-asserted-by":"publisher","unstructured":"De Souza, G.A., Da Costa-Abreu, M.: Automatic offensive language detection from Twitter data using machine learning and feature selection of metadata. In: 2020 IJCNN, pp. 1\u20136. IEEE (2020). https:\/\/doi.org\/10.1109\/IJCNN48605.2020.9207652","DOI":"10.1109\/IJCNN48605.2020.9207652"},{"issue":"1","key":"21_CR10","doi-asserted-by":"publisher","first-page":"525","DOI":"10.11591\/ijece.v9i1.pp525-530","volume":"9","author":"MA Fauzi","year":"2019","unstructured":"Fauzi, M.A.: Word2Vec model for sentiment analysis of product reviews in Indonesian language. In. J. Electr. Comput. Eng. (IJECE) 9(1), 525 (2019). https:\/\/doi.org\/10.11591\/ijece.v9i1.pp525-530","journal-title":"In. J. Electr. Comput. Eng. (IJECE)"},{"key":"21_CR11","unstructured":"Fbi: How Do Violent Extremists Make Contact? (2021). https:\/\/www.fbi.gov\/cve508\/teen-website\/how"},{"key":"21_CR12","unstructured":"Gaydhani, A., Doma, V., Kendre, S., Bhagwat, L.: Detecting hate speech and offensive language on Twitter using machine learning: an N-gram and TFIDF based approach (2018)"},{"key":"21_CR13","unstructured":"Internet World Stats: Internet Usage Statistics; The Internet Big Picture; World Internet Users and 2021 Population Stats (2021). https:\/\/www.internetworldstats.com\/stats.htm"},{"key":"21_CR14","unstructured":"Jacobo, J.: This is what Trump told supporters before many stormed Capitol Hill. ABC News (2021). https:\/\/tinyurl.com\/w5aaar5c"},{"issue":"8","key":"21_CR15","doi-asserted-by":"publisher","first-page":"e0220,976","DOI":"10.1371\/journal.pone.0220976","volume":"14","author":"B Jang","year":"2019","unstructured":"Jang, B., Kim, I., Kim, J.W.: Word2vec convolutional neural networks for classification of news articles and tweets. PLOS One 14(8), e0220,976 (2019). https:\/\/doi.org\/10.1371\/journal.pone.0220976","journal-title":"PLOS One"},{"key":"21_CR16","doi-asserted-by":"publisher","first-page":"100,057","DOI":"10.1016\/j.yjbinx.2019.100057","volume":"4","author":"FK Khattak","year":"2019","unstructured":"Khattak, F.K., Jeblee, S., Pou-Prom, C., Abdalla, M., Meaney, C., Rudzicz, F.: A survey of word embeddings for clinical text. J. Biomed. Inf. X 4, 100,057 (2019). https:\/\/doi.org\/10.1016\/j.yjbinx.2019.100057","journal-title":"J. Biomed. Inf. X"},{"key":"21_CR17","doi-asserted-by":"crossref","unstructured":"Kula, S., Chora\u015b, M., Kozik, R.: Application of the BERT-based architecture in fake news detection. In: Conference on Complex, Intelligent, and Software Intensive Systems, pp. 239\u2013249. Springer (2020)","DOI":"10.1007\/978-3-030-57805-3_23"},{"key":"21_CR18","unstructured":"Lewis, R.: Alternative influence; Broadcasting the reactionary right on YouTube. Data & Society (2018). https:\/\/tinyurl.com\/4pys8w93"},{"issue":"2010","key":"21_CR19","first-page":"627","volume":"2","author":"B Liu","year":"2010","unstructured":"Liu, B.: Sentiment analysis and subjectivity. Handb. Nat. Lang. Process. 2(2010), 627\u2013666 (2010)","journal-title":"Handb. Nat. Lang. Process."},{"key":"21_CR20","unstructured":"Lyons, D.: The 6 hardest languages For English speakers to learn. Babbel Magazine (2021). https:\/\/tinyurl.com\/drb83774"},{"key":"21_CR21","doi-asserted-by":"publisher","unstructured":"Ma, L., Zhang, Y.: Using Word2Vec to process big text data. In: 2015 IEEE International Conference on Big Data (Big Data), pp. 2895\u20132897. IEEE (2015). https:\/\/doi.org\/10.1109\/BigData.2015.7364114","DOI":"10.1109\/BigData.2015.7364114"},{"key":"21_CR22","unstructured":"McDonald, S., Ramscar, M.: Testing the distributioanl hypothesis: the influence of context on judgements of semantic similarity. In: Proceedings of the Annual Meeting of the Cognitive Science Society, vol. 23 (2001)"},{"key":"21_CR23","unstructured":"Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space (2013). http:\/\/arxiv.org\/abs\/1301.3781"},{"key":"21_CR24","doi-asserted-by":"publisher","unstructured":"Mussiraliyeva, S., Bolatbek, M., Omarov, B., Medetbek, Z., Baispay, G., Ospanov, R.: On detecting online radicalization and extremism using natural language processing. In: 2020 21st International Arab Conference on Information Technology (ACIT), pp. 1\u20135. IEEE (2020). https:\/\/doi.org\/10.1109\/ACIT50332.2020.9300086","DOI":"10.1109\/ACIT50332.2020.9300086"},{"key":"21_CR25","doi-asserted-by":"publisher","unstructured":"Nugroho, K., et al.: Improving random forest method to detect hatespeech and offensive word. In: 2019 ICOIACT, pp. 514\u2013518. IEEE (2019). https:\/\/doi.org\/10.1109\/ICOIACT46704.2019.8938451","DOI":"10.1109\/ICOIACT46704.2019.8938451"},{"issue":"21","key":"21_CR26","doi-asserted-by":"publisher","first-page":"4654","DOI":"10.3390\/s19214654","volume":"19","author":"JC Pereira-Kohatsu","year":"2019","unstructured":"Pereira-Kohatsu, J.C., Quijano-S\u00e1nchez, L., Liberatore, F., Camacho-Collados, M.: Detecting and monitoring hate speech in Twitter. Sensors 19(21), 4654 (2019). https:\/\/doi.org\/10.3390\/s19214654","journal-title":"Sensors"},{"issue":"12","key":"21_CR27","doi-asserted-by":"publisher","first-page":"4730","DOI":"10.1007\/s10489-018-1242-y","volume":"48","author":"GK Pitsilis","year":"2018","unstructured":"Pitsilis, G.K., Ramampiaro, H., Langseth, H.: Effective hate-speech detection in Twitter data using recurrent neural networks. Appl. Intell. 48(12), 4730\u20134742 (2018). https:\/\/doi.org\/10.1007\/s10489-018-1242-y","journal-title":"Appl. Intell."},{"key":"21_CR28","unstructured":"Ran: Extremists\u2019 Use of Video Gaming - Strategies and Narratives (2020)"},{"key":"21_CR29","unstructured":"Staudemeyer, R.C., Morris, E.R.: Understanding LSTM - a tutorial into long short-term memory recurrent neural networks (2019)"},{"key":"21_CR30","unstructured":"The Washington Post: How rumors on WhatsApp led to a mob killing in India | The Fact Checker. The Washington Post (2020)"},{"key":"21_CR31","unstructured":"United Nations Organization: United Nations Strategy and Plan of Action on Hate Speech (2020)"},{"issue":"11","key":"21_CR32","doi-asserted-by":"publisher","first-page":"39","DOI":"10.22215\/timreview\/1282","volume":"9","author":"M Westerlund","year":"2019","unstructured":"Westerlund, M.: The emergence of deepfake technology: a review. Technol. Innov. Manage. Rev. 9(11), 39\u201352 (2019). https:\/\/doi.org\/10.22215\/timreview\/1282","journal-title":"Technol. Innov. Manage. Rev."}],"container-title":["Lecture Notes in Networks and Systems","Progress in Image Processing, Pattern Recognition and Communication Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-81523-3_21","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,8,17]],"date-time":"2021-08-17T17:18:48Z","timestamp":1629220728000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-81523-3_21"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,18]]},"ISBN":["9783030815226","9783030815233"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-81523-3_21","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"type":"print","value":"2367-3370"},{"type":"electronic","value":"2367-3389"}],"subject":[],"published":{"date-parts":[[2021,8,18]]},"assertion":[{"value":"18 August 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CORES","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computer Recognition Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 June 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 June 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cores2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/cores.pwr.edu.pl","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}