The hospitality sector generates a lot of data, which is added as written feedbacks and/or numerical ratings. Online travel agencies (OTAs) thrive on giving consumers a variety of options tailored according to their tastes and needs. In this research, we propose ranking of hotels according to customer provided reviews. The whole process is carried out using several techniques. The reviews are initially pre-processed and a topic modelling technique Latent Dirichlet Allocation (LDA) has been utilized to extract important features. Maximum Entropy Minimum Variance Ordered Weighted Averaging (MEMV-OWA) method is then utilized to assign weights to individual topics. For ranking, multi-criteria decision-modelling approach Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is utilized. To address the imprecision inherent in human judgement, picture fuzzy numbers are used. The findings of the research provide theoretical and practical implementations and are discussed in the paper.