Abstract
Online reviews have become crucial in the hospitality industry, driving hotels to improve their online reputation by responding effectively to guest feedback. However, the responding behaviour of managers remains a mystery, especially in the African context. In this paper, by collecting TripAdvisor data, we aim to use text mining and natural language processing to uncover the responding behaviour of African hotel managers, making us among the first researchers to tackle this topic in the African context. Our study sheds light on the critical factors that describe the responding behaviour of African hotel managers, including response priority, length, speed, ratio, sentiment, diversity and similarity. We examine the influence of review length, sentiment, and the reviewer's traveller type (e.g., business travellers) on this response behaviour. Further, we explore the externalities of this responding behaviour on subsequent review ratings.