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Most tasks regarding natural language processing are addressed using traditional machine learning methods and static datasets. This setting can lead to several problems, e.g., outdated datasets and models, which degrade in performance over time. This is particularly true regarding concept drift, in which the data distribution changes over time. Furthermore, text streaming scenarios also exhibit further challenges, such as the high speed at which data arrive over time. Models for stream scenarios must adhere to the aforementioned constraints while learning from the stream, thus storing texts for limited periods and consuming low memory. This study presents a systematic literature review regarding concept drift adaptation in text stream scenarios. Considering well-defined criteria, we selected 48 papers published between 2018 and August 2024 to unravel aspects such as text drift categories, detection types, model update mechanisms, stream mining tasks addressed, and text representation methods and their update mechanisms. Furthermore, we discussed drift visualization and simulation and listed real-world datasets used in the selected papers. Finally, we brought forward a discussion on existing works in the area, also highlighting open challenges and future research directions for the community.<\/jats:p>","DOI":"10.1145\/3704922","type":"journal-article","created":{"date-parts":[[2024,11,21]],"date-time":"2024-11-21T11:32:07Z","timestamp":1732188727000},"page":"1-67","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":10,"title":["Concept Drift Adaptation in Text Stream Mining Settings: A Systematic Review"],"prefix":"10.1145","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7475-146X","authenticated-orcid":false,"given":"Cristiano Mesquita","family":"Garcia","sequence":"first","affiliation":[{"name":"Instituto Federal de Santa Catarina, Ca\u00e7ador, Brazil and Programa de P\u00f3s-Gradua\u00e7\u00e3o em Inform\u00e1tica, Pontif\u00edcia Universidade Cat\u00f3lica do Paran\u00e1, Curitiba, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7197-5951","authenticated-orcid":false,"given":"Ramon","family":"Abilio","sequence":"additional","affiliation":[{"name":"Instituto Federal de S\u00e3o Paulo, Capivari, Brazil and Programa de P\u00f3s-Gradua\u00e7\u00e3o em Tecnologia, Universidade Estadual de Campinas, Limeira, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5879-7014","authenticated-orcid":false,"given":"Alessandro Lameiras","family":"Koerich","sequence":"additional","affiliation":[{"name":"\u00c9cole de Technologie Sup\u00e9rieure, Universit\u00e9 du Qu\u00e9bec, Montr\u00e9al, Quebec, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3064-3563","authenticated-orcid":false,"suffix":"Jr","given":"Alceu de Souza","family":"Britto","sequence":"additional","affiliation":[{"name":"Programa de P\u00f3s-Gradua\u00e7\u00e3o em Inform\u00e1tica, Pontif\u00edcia Universidade Cat\u00f3lica do Paran\u00e1, Curitiba, Brazil and Universidade Estadual de Ponta Grossa, Ponta Grossa, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9928-854X","authenticated-orcid":false,"given":"Jean Paul","family":"Barddal","sequence":"additional","affiliation":[{"name":"Programa de P\u00f3s-Gradua\u00e7\u00e3o em Inform\u00e1tica, Pontif\u00edcia Universidade Cat\u00f3lica do Paran\u00e1, Curitiba, Brazil"}]}],"member":"320","published-online":{"date-parts":[[2025,2,5]]},"reference":[{"key":"e_1_3_2_2_2","unstructured":"Mart\u00edn Abadi Ashish Agarwal Paul Barham Eugene Brevdo Zhifeng Chen Craig Citro Greg S. 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