标题： 通过时空交互模型重新审视国际新闻流理论 显示英文标题

标题： International news flows theory revisited through a space-time interaction model

摘要： 本文提出了一种基于时间、媒体和相关国家的离散空间相互作用重力模型的外国新闻流通定量模型。 对2015年31家日报发布的国际RSS新闻故事的分析表明，首先，Galtung和Ruge以及Östgaard半个世纪前预测的许多国际新闻传播定律仍然有效。 媒体中国家的显著性仍由规模效应（面积、人口）强烈决定，富裕国家（人均GDP）和具有精英地位的国家（联合国安理会常任理事国、教廷）受到突出报道。 地理距离和共同语言的影响仍然是新闻编辑室媒体覆盖的主要因素。 与平坦世界假说相矛盾的是，全球新闻业仍然是例外，地方主义是常态。 按媒体对模型进行离散化分析表明，报纸并不完全遵循相同的规则，对距离、共同语言或精英地位的敏感程度各不相同。 按周对模型进行离散化分析表明，影响外国新闻的规则也可能因特殊事件而暂时改变，这些事件消除了显著性和相关性的通常影响，产生短暂的“全球共识”时期，这可能使小国、贫穷国家和偏远国家受益。 本文最后建议，在全球研究中应使用精心选择的多样化媒体样本，而不是大量数据的聚合。 显示英文摘要

摘要： This paper proposes a quantitative model of the circulation of foreign news based on a gravity-like model of spatial interaction disaggregated by time, media and countries of interest. The analysis of international RSS news stories published by 31 daily newspapers in 2015 demonstrates, first, that many of the laws of circulation of international news predicted half a century ago by Galtung and Ruge and by {\"O}stgaard are still valid. The salience of countries in media remains strongly determined by size effects (area, population), with prominent coverage of rich countries (GDP/capita) with elite status (permanent members of UNSC, the Holy See). The effect of geographical distance and a common language remains a major factor of media coverage in newsrooms. Contradicting the flat world hypothesis, global journalism remains an exception, and provincialism is the rule. The disaggregation of the model by media demonstrates that newspapers are not following exactly the same rules and are more or less sensitive to distance, a common language or elite status. The disaggregation of the model by week suggests that the rules governing foreign news can also be temporarily modified by exceptional events that eliminate the usual effects of salience and relatedness, producing short periods of 'global consensus' that can benefit small, poor and remote countries. This paper concludes by recommending the use of a sample of carefully chosen diversified media rather than a large aggregation of data for global studies.