Abstract
Social networking platforms facilitate sharing of information, ideas, and thoughts by constructing virtual communities. Finding people in certain social networking sites, who really have the power to influence other users, is critical. For example, this search can be focused on the right person who can impactfully support or contradict any opinion or generate more profits when they publish an advertisement for a certain business or product. The aim of this study is to devise a computational method of finding the most influential users on social networking platforms. In this study, we propose a solution named Muatheer, which helps determine who influential users are on Instagram. The study uses techniques of scraping data using Instagram Application Programming Interface (API) and applying the sentiment analysis algorithm to classify comments as either positive or negative. The study also uses the unigram as a feature extraction method. Then, the sentiment analysis result will be combined with other factors to calculate the "influence ratio", which attempts to determine the actual influencer in a specific domain. These experiments were conducted using a publicly available datasets from Instagram, and the proposed algorithm delivered a highly accurate result more than 85 %. Povzetek: