Organizations seeking to improve user engagement continue to invest in fan pages on social media platforms anticipating that in a progressive global marketplace users will utilize these technologies, which will enhance organizational competitive advantages. With the steady growth of the number of users who followed firm fan pages it is not clear whom should firms listen to? Since fan page followers participate and contribute on fan pages in various ways, a one size fits all strategy to select users to follow them back may not work. To address these issues, we focus on firm fan pages on Twitter. Using tweets generated by active users on fan pages, this study examines firms’ strategy of following back users on their fan pages. We examine users based on their activities, nature, and sentiments of their contents created and disseminated. We apply topic modeling and sentiment analysis to the tweets of two prominent airline fan pages in pacific region. We discuss the results obtained from a set of almost 21277 tweets of the 4735 active users. Our results show that automated categorization via LDA-based topic modeling and sentiment analysis of the users tweets can help firms select whom to follow back. We find that firms follow back their users based on a mix of users’ activities, topic of content created or disseminated and sentiments of their contents. Results and managerial implications are discussed. The outcomes of this paper help businesses to invest wisely on their social media activities and specif-ically fan page management.