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In Proceedings of the National Academy of Sciences of the United States of America

Major changes to the operation of local newsrooms-ownership restructuring, layoffs, and a reorientation away from print advertising-have become commonplace in the last few decades. However, there have been few systematic attempts to characterize the impact of these changes on the types of reporting that local newsrooms produce. In this paper, we propose a method to measure the investigative content of news articles based on article text and influence on subsequent articles. We use our method to examine over-time and cross-sectional patterns in news production by local newspapers in the United States over the past decade. We find surprising stability in the quantity of investigative articles produced over most of the time period examined, but a notable decline in the last 2 y of the decade, corresponding to a recent wave of newsroom layoffs.

Turkel Eray, Saha Anish, Owen Rhett Carson, Martin Gregory J, Vasserman Shoshana


journalistic impact, local news, machine learning