Working paper title: Platform Power in News Aggregation

By: Ruben Durante, Ruben Enikolopov, Daniil Mikhailov, & Andrey Simono

Abstract

News aggregators are among the primary gatekeepers of online news, shaping both consumption and production through the algorithms that rank stories and sources. We provide the first large-scale estimates of this algorithmic power using Yandex News, Russia’s largest aggregator. Combining snapshots of its front-page rankings with 12.3 million articles from 50 outlets and daily traffic data, we estimate that a front-page reference generates roughly 380,000 additional daily visitors for an outlet—an effect that is stable across news topics, event types, and consumer demographics. Exploiting a 2016 Russian law that made aggregators liable for cited content as a natural experiment, we show that Yandex halved its references to independent outlets, redistributing traffic by up to 27% across outlets. Consumers did not penalize this manipulation: referred outlets continued to capture the same share of front-page visitors. Outlets removed from the rankings subsequently shifted toward longer articles and stopped optimizing headlines for the algorithm, showing that aggregator algorithms affect not only consumption but also production incentives.