Now-a-days, social network sites have become quite popular for communication in the society. People have entangled their day-to-day activities around social media platforms. Social Networks have allowed the users to share their opinions on different topics. In social media, sentiment analysis is an important character to determine opinions of users. Moreover, user’s can be ranked to determine their relative influence. This paper proposes a methodology to rank the users involving sentiment related parameters such as likes, comments and corresponding likescount. Analysis of users’ comments is carried-out. Weights are assigned to these parameters and scores are calculated for each user. Users are ranked on the basis of scores obtained and compared with existing technique. In order to verify the effectiveness of proposed methodology, data is extracted from a verified Facebook page ‘Panjab University, Chandigarh’. Mean, standard deviation and variance are computed to capture the usefulness of ranks obtained by the proposed method. Results depict that the proposed methodology is better than existing technique since it incorporates several features indicating positive and negative behavior of users. This technique can be used to determine the highly trusted and the most distrusted users in a social media user’s profile. Users with negative scores can be considered for outlier analysis. The proposed methodology can also be extended to work on other social media platforms. © 2017, Springer Science+Business Media New York.