Movie Account Recommendation on Instagram

Abstract

With the increasing popularity of social networks, many businesses have started implementing their branding or targeted advertising strategies to reach potential customers through social media platforms. It is desirable and essential to help businesses to reach mass audiences and assist users to find favorite business accounts on social media platforms. In the movie industry, movie companies often create business accounts (movie accounts) to promote their movies and capture the attention of followers on Instagram. Instagram contains rich information about movies and user feedback, while IMDb, one of the most popular online databases, contains well-organized information related to movies. The features extracted from the data collected from Instagram and IMDb can complement each other. Therefore, in this study, we propose a framework for recommending movie accounts to users on Instagram by using the data collected from Instagram and IMDb platforms. The experiment results show that our proposed framework outperforms the comparing methods in terms of precision, recall, F1-score, and Normalized Discounted Cumulative Gain (NDCG), and mitigates the effect of cold start problems. The proposed framework can help movie companies or businesses reach potential audiences and implement effective targeted advertising strategies.