Public Service Media, Diversity and Algorithmic Recommendation: Tensions between Editorial Principles and Algorithms in European PSM Organizations
Public Service Media, Diversity and Algorithmic Recommendation: Tensions between Editorial Principles and Algorithms in European PSM Organizations
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公共服务媒体、多样性和算法推荐：欧洲 PSM 组织编辑原则和算法之间的紧张关系
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
J. Sørensen
中科院分区：
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作者：
J. Sørensen
公共服务媒体（PSM）网站是实施媒体个性化推荐系统的一个有趣案例，因为PSM组织需要平衡曝光优化与传统但定义不清的PSM政策目标，如公平，观点多样性和透明度。此外，推荐系统的数学逻辑需要适应传统的广播调度和发布策略和过程。最后，随着PSM组织进入新的领域，推荐系统技术的驯化和适应必须发生，而PSM组织试图拥抱与推荐系统相关的新知识和新专业。基于2016年12月至2019年4月进行的25次深度访谈，本文对来自8个国家的9家欧洲公共服务媒体组织的推荐系统实施情况进行了跨欧洲分析。调查结果表明，PSM组织，虽然个性化的竞争必要性，方法推荐系统犹豫，以保持核心PSM的价值观在网上环境。此外，尽管PSM组织选择的协同过滤表明了以用户为中心的方法，但推荐系统之上的策展系统重新安装了以广播公司为中心的方法。
Public Service Media (PSM) websites are an interesting case for the implementation of recommender systems for media personalization, as the PSM organizations need to balance the optimization of exposure with traditional but ill-defined PSM policy goals such as fairness, viewpoint diversity and transparency. Furthermore, the mathematical logic of recommender system needs to be adapted to the legacy broad-casting scheduling and publishing strategies and procedures. Finally, as the PSM organizations step into new territories, domestication and adaption of the recommender system technologies must take place while PSM organizations try to embrace the new knowledge and new professions associated with recommender systems. Based on 25 in-depth interviews conducted from December 2016 to April 2019, this paper presents a cross-European analysis of the implementation of recommender systems in nine European public service media organizations from eight countries. The findings indicate that PSM organizations, although viewing personalisation as competitive necessity, approach recommendation systems with hesitation in order to maintain core PSM-values in the online environment. Furthermore, although the collaborative filtering chosen by the PSM organizations indicate a user-centered approach, curation systems on top of recommender systems re-install a broadcaster-centric approach.