The revolution of social media has propelled the online community to take advantage of online reviews for not only posting feedback about the products, services, and other issues but also assists individuals to analyze user’s feedback for making purchase decisions, and companies for improving the quality of manufactured goods. However, the propagation of fake reviews has become an alarming issue, as it deceives online users while purchasing and promotes or demotes the reputation of competing brands. In this work, we propose a supervised learning-based technique for the detection of fake reviews from the online textual content. The study employs machine learning classifiers for bifurcating fake and genuine reviews. Experimental results are evaluated against different evaluation measures and the performance of the proposed system is compared with baseline works. © 2021, Springer Nature Switzerland AG.