A Recommendation Algorithm Based on User's Behaviours in Social Networks
Anh Nguyen Duy, Tien Nguyen Van · 2023
The advent of social networks is currently regarded as the most significant development for internet users. Prominent online social platforms like Facebook, Twitter and LinkedIn have gained popularity and trans-formed conventional communication methods. The interactions among individuals within these social networks create a diverse and abundant resource, presenting valuable opportunities for analysis, exploration and application development. This paper proposes a collaborative filtering approach that integrates user behaviours on social networks. This approach analyzes user sentiments expressed through rating, posting, liking and commenting within the social network. Based on the insights derived from these sentiment analyses, we put forth algorithms for recommending appropriate content to individual users. Experimental results using real datasets collected from Facebook social networks demonstrate that our proposed methods outperform trust model-based approaches.