Analysis of the Development Status and Path of Media Convergence Based on Personalized Recommendation Algorithm: Case Study of Dalian News Media Group

Abstract

With the development of big data, artificial intelligence, and 5G technology, the media has gradually become intelligent. Various types of social media have used algorithmic technology to provide users with personalized recommendations. The long-lasting content ecology and communication mechanism will face reconstruction. This article analyzes the impact of personalized recommendation algorithms on user acquisition, consumption and sharing of content, and focus on Dalian News Media Group to analyze the development status and existing problems of its media convergence, and then analyzes the development path of its media convergence based on the personalized recommendation algorithm. First of all, the way of media convergence should be conversed from top to bottom to advance the integration of depth and breadth. Secondly, establishing user thinking on the basis of building a new media matrix, combined with the behavioral characteristics of users for accurate recommendation. Finally, we must pay attention to all media personnel training, the introduction of talent incentive mechanism, and to enhance public information literacy education in new media.