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In this paper, we present an approach to classify argumentative components using language models and machine learning algorithms on a new corpus of academic theses and research proposals. We explore the use of lexical, syntactic, semantic and indicator features to tackle this task. We found that lexical features provide the best efficacy for the classification. For language models, the best features were syntactical. But our experiments showed that a document occurrence representation with unigrams achieved the best accuracy. We also tested the conclusions about the representation and classifier on theses according to their study level (undergraduate, master, and doctoral). We analyzed the information gain of features and found patterns that are part of argumentative markers.<\/jats:p>","DOI":"10.3233\/jifs-169488","type":"journal-article","created":{"date-parts":[[2018,5,18]],"date-time":"2018-05-18T10:38:43Z","timestamp":1526639923000},"page":"3037-3047","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":3,"title":["Argument component classification in academic writings"],"prefix":"10.1177","volume":"34","author":[{"given":"Jes\u00fas Miguel","family":"Garcia-Gorrostieta","sequence":"first","affiliation":[{"name":"Department of Computational Sciences, National Institute of Astrophysics, Optics and Electronics, Tonantzintla, Puebla, M\u00e9xico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aurelio","family":"L\u00f3pez-L\u00f3pez","sequence":"additional","affiliation":[{"name":"Department of Computational Sciences, National Institute of Astrophysics, Optics and Electronics, Tonantzintla, Puebla, M\u00e9xico"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2018,5,17]]},"reference":[{"key":"e_1_3_3_2_2","first-page":"183","volume-title":"In Proceedings of the Seventeenth Conference on Computational Natural Language Learning","author":"Al-Rfou R.","year":"2013","unstructured":"Al-RfouR., PerozziB. and SkienaS., Polyglot: Distributed word representations for multilingual nlp, In Proceedings of the Seventeenth Conference on Computational Natural Language Learning , Sofia, Bulgaria. 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