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In most cases, a question in a web forum receives several responses, making it impossible for the question poster to obtain the most suitable answer. Thus, an important problem is how to automatically extract the most appropriate and high\u2010quality answers in a thread. Prior studies have used different combinations of both lexical and nonlexical features to retrieve the most relevant answers from discussion forums, and hence, there is no standard\/general set of features that could be effectively used for relevant answer\/reply post classification. However, this study proposed an answer detection model that is exclusively relying on lexical features and employs a random forest classifier for classification of answers in discussion boards. Experimental results showed that the proposed answer detection model outperformed the baseline technique and other state\u2010of\u2010the\u2010art machine learning algorithms in terms of classification accuracy on benchmark forum datasets.<\/jats:p>","DOI":"10.1155\/2021\/2893257","type":"journal-article","created":{"date-parts":[[2021,4,15]],"date-time":"2021-04-15T22:17:36Z","timestamp":1618525056000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Impact of Lexical Features on Answer Detection Model in Discussion Forums"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3628-0262","authenticated-orcid":false,"given":"Atif","family":"Khan","sequence":"first","affiliation":[]},{"given":"Muhammad Adnan","family":"Gul","sequence":"additional","affiliation":[]},{"given":"Abdullah","family":"Alharbi","sequence":"additional","affiliation":[]},{"given":"M. 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