公益广告突破算法推荐壁垒的传播策略研究

Research on Communication Strategies for Public Service Advertisements to Break through Algorithmic Recommendation Barriers

摘要: 在智能时代，算法推荐技术成为信息传播核心驱动力，深刻改变信息分发模式。公益广告作为传播社会主流价值观、推动精神文明建设的重要载体，却在传播过程中受到限制，没有达到良好的传播效果。因此，理清公益广告与算法推荐之间的耦合机制对促进公益广告传播生态良性发展具有重要意义。研究发现，算法推荐的协同过滤算法、标签机制、爆款导向等机制限制了公益广告的传播范围和传播效果。对此，公益广告突破算法推荐机制可从以下两个思路入手：一是，公益广告主动适配算法规则；二是，平台强化责任意识与算法推荐优化，从而构建“内驱力–外驱力”协同的突破策略，推动公益理念广泛传播与落地。

Abstract: In the intelligent era, algorithmic recommendation technology has become the core driving force of information dissemination, profoundly reshaping the mode of information distribution. As an important vehicle for disseminating mainstream social values and promoting spiritual civilization development, public service advertisements (PSAs) face limitations in their communication process and fail to achieve satisfactory outreach. Therefore, clarifying the coupling mechanism between PSAs and algorithmic recommendation is of great significance for fostering the healthy development of the PSA communication ecosystem. Research finds that mechanisms such as collaborative filtering algorithms, tagging mechanisms, and popularity-driven orientation within algorithmic recommendation systems restrict the reach and effectiveness of PSAs. To address this, breaking through the algorithmic recommendation barriers can be approached from two perspectives: first, PSAs proactively adapting to algorithmic rules; second, platforms strengthening their sense of responsibility and optimizing algorithmic recommendations. This facilitates the construction of a breakthrough strategy synergizing “internal drive—external drive”, thereby promoting the widespread dissemination and implementation of public welfare concepts.