Abikoye, Oluwakemi ChristianaOmokanye, Samuel OladejiAro, Taye Oladele2018-05-212018-05-212018-05Abikoye, O.C., Omokanye, S.O. & Aro, T.O. (2018): Text Classification Using Data Mining Techniques: A Review. Computing and Information Systems Journal. 22(2); 1- 8, Published by School of Computing, Engineering and Physical Science, University of the West of Scotland, Paisley.1352-9404http://hdl.handle.net/123456789/244mining algorithms used for text classification and a review of works that have been performed on classifying texts. Design/Methodology/Approach: Data mining algorithms used for text classification were discussed and researches done on applying such algorithms in classifying texts were considered with more emphasis on comparative studies. Findings: No classifier can perform best in all situations as different datasets and conditions bring about different classification accuracies. Practical Implications: In applying data mining algorithms for classifying text documents, it should be noted that the conditions of the data will affect classification accuracy; therefore such data should be well presented. Researchers may also need to try different algorithms and conditions to get a desired level of accuracy. Originality/Value: A lot of work has been done in reviewing of data mining algorithms but this research has its specific emphasis on text and in addition to previous reviews, more recent journals were consideredenData miningText miningtext classificationperformance evaluationclassifiermachine learning algorithm (MLA).Article