Concentration without cumulative advantage: the distribution of news source attention in online communities

JOURNAL OF COMMUNICATION(2022)

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摘要
Many attention markets exhibit stable patterns of concentration, where a few producers attract and sustain a far greater share of the audience than others. This inequality often follows patterns consistent with cumulative advantage, a process in which performance compounds over time. Attention to news sources online possesses these characteristics; however, online audiences also fragment across many disparate news producers. How do social media and recommender systems contribute to these attention dynamics? In this study, we examine two paradigmatic models: concentration driven by cumulative advantage and fragmentation driven by stochasticity. We evaluate these models against a large-scale empirical dataset of news source attention in the popular social media site Reddit. While we find high levels of attention concentration, we do not find the stable popularity over time that characterizes cumulative advantage. Rather, sources gain and lose popularity seemingly at random, aligning with a stochastic model. These results demonstrate the persistence of attention inequality, even in the absence of a strong driving mechanism. They also suggest that social media systems can undermine the accumulation of attention to the most prominent news sources. Digital attention markets striving for more equitable allocation require novel mechanisms of organizing and distributing information.
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关键词
digital news, cumulative advantage, news audiences, computational methods, social media
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