论文标题
在线新闻影响动态的简单规律性
Simple regularities in the dynamics of online news impact
论文作者
论文摘要
在线新闻可以迅速到达并影响数百万的人，但我们还不知道是否存在潜在的动态规律来控制它们对公众的影响。我们使用来自BBC和New York Times的两个主要新闻媒体的数据，其中用户评论的数量可以用作新闻影响的代表。我们发现，在线新闻文章的影响动态并未在许多其他社会和信息系统中显示出流行的模式。特别是，我们发现简单的指数分布比幂律分布更适合经验新闻影响分布。该观察结果是通过分析数据中原本无所不在的丰富富富机制的缺乏或有限的影响来解释的。新闻影响的时间动态表现出了普遍的指数衰减，使我们能够将单个新闻轨迹崩溃成基本的单曲线。我们还展示了用户活动的每日变化如何直接影响文章影响的动态。我们的发现挑战了在其他社会环境中发现的流行动态模式的普遍适用性。
Online news can quickly reach and affect millions of people, yet we do not know yet whether there exist potential dynamical regularities that govern their impact on the public. We use data from two major news outlets, BBC and New York Times, where the number of user comments can be used as a proxy of news impact. We find that the impact dynamics of online news articles does not exhibit popularity patterns found in many other social and information systems. In particular, we find that a simple exponential distribution yields a better fit to the empirical news impact distributions than a power-law distribution. This observation is explained by the lack or limited influence of the otherwise omnipresent rich-get-richer mechanism in the analyzed data. The temporal dynamics of the news impact exhibits a universal exponential decay which allows us to collapse individual news trajectories into an elementary single curve. We also show how daily variations of user activity directly influence the dynamics of the article impact. Our findings challenge the universal applicability of popularity dynamics patterns found in other social contexts.
