Social Media Recommendation Systems Knowledge Graph Trends

Abstract

This paper conducts a systematic analysis of research on social media recommendation algorithms within the field of journalism using bibliometric methods. The goal is to uncover research hotspots, developmental trends, and application scenarios in this area. By applying citation analysis, keyword analysis, and network structure analysis in bibliometrics, the study examines the disciplinary distribution, core themes, and research frontiers of social media recommendation algorithms in journalism. The findings show that research on recommendation algorithms in journalism primarily focuses on information dissemination and user behavior analysis, with significant impacts on news communication, social interaction, and public opinion management. This study provides theoretical support for understanding the development trajectory of recommendation algorithms in communication studies and proposes new directions for future research.