A method for measuring investigative journalism in local newspapers
Rhett Carson Owen,
Gregory J. Martin and
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Anish Saha: Graduate School of Business, Stanford University, Stanford, CA 94305
Rhett Carson Owen: Graduate School of Business, Stanford University, Stanford, CA 94305
Gregory J. Martin: Graduate School of Business, Stanford University, Stanford, CA 94305
Proceedings of the National Academy of Sciences, 2021, vol. 118, issue 30, e2105155118
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.
Keywords: journalistic impact; local news; machine learning (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:nas:journl:v:118:y:2021:p:e2105155118
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