The purpose of this paper is to develop a conceptual framework for assessing what are the possibilities and pitfalls of using algorithmic systems of news personalization – i.e. the tailoring of individualized news feeds based on users’ information preferences – for constructive conflict coverage in the context of peace journalism, a journalistic paradigm calling for more diversified and creative war reporting.,The paper provides a critical review of existing research on peace journalism and algorithmic news personalization, and analyzes the intersections between the two concepts. Specifically, it identifies recurring pitfalls of peace journalism based on empirical research on constructive conflict coverage and then introduces a conceptual framework for analyzing to what degree these pitfalls can be mediated – or worsened – through algorithmic system design.,The findings suggest that AI-driven distribution technologies can facilitate constructive war reporting, in particular by countering the effects of journalists’ self-censorship and by diversifying conflict coverage. The implementation of these goals, however, depends on multiple system design solutions, thus resonating with current calls for more responsible and value-sensitive algorithmic design in the domain of news media. Additionally, our observations emphasize the importance of developing new algorithmic literacies among journalists both to realize the positive potential of AI for promoting peace and to increase the awareness of possible negative impacts of new systems of content distribution.,The article particle is the first to provide a comprehensive conceptualization of the impact of new content distribution techniques on constructive conflict coverage in the context of peace journalism. It also offers a novel conceptual framing for assessing the impact of algorithmic news personalization on reporting traumatic and polarizing events, such as wars and violence.

中文翻译：

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和平新闻个性化：算法建议如何影响冲突报道

本文的目的是建立一个概念框架，以评估使用新闻个性化算法系统（即根据用户的信息偏好定制个性化新闻源）在和平背景下进行建设性冲突的可能性和陷阱新闻学，一种新闻范式，要求进行更加多样化和创造性的战争报道。本文对和平新闻学和算法新闻个性化的现有研究进行了批判性综述，并分析了这两个概念之间的交集。特别，它基于对建设性冲突报道的实证研究，确定了和平新闻的反复出现的陷阱，然后引入了一个概念框架，用于分析这些陷阱可以通过算法系统设计在多大程度上被介导或恶化。研究结果表明，人工智能驱动的分配技术可以促进建设性的战争报道，特别是通过抵抗记者自我审查的影响和使冲突报道多样化。但是，这些目标的实现取决于多种系统设计解决方案，因此与新闻媒体领域对当前负责任的，对价值更敏感的算法设计的当前需求产生了共鸣。另外，我们的观察结果强调了在新闻工作者中开发新算法素养的重要性，既要认识到AI促进和平的积极潜力，也要提高人们对新内容分发系统可能产生的负面影响的认识。在和平新闻背景下，对新的内容分发技术对建设性冲突报道的影响进行概念化。它还提供了新颖的概念框架，用于评估算法新闻个性化对报道战争和暴力等创伤性和两极分化事件的影响。本文的第一篇文章首次全面介绍了新的内容分发技术对和平新闻背景下建设性冲突报道的影响。它还提供了新颖的概念框架，用于评估算法新闻个性化对报道战争和暴力等创伤性和两极分化事件的影响。本文的第一篇文章首次全面介绍了新的内容分发技术对和平新闻背景下建设性冲突报道的影响。它还提供了新颖的概念框架，用于评估算法新闻个性化对报道战争和暴力等创伤性和两极分化事件的影响。