Does Local News Stay Local?: Online Content Shifts in Sinclair-Acquired Stations

TL;DR

This study investigates how Sinclair Broadcast Group's acquisition of local TV stations affects the content of local news. Using YouTube transcripts from eight Sinclair stations and two national outlets, the authors combine log-odds word-shift analysis (Fightin' Words) with structured topic modeling (STM) to quantify shifts in overall topic prevalence and the politicization of topics before versus after purchase. They further employ Word2Vec embeddings to examine how politicized terms shift in meaning and contextual associations, comparing local stations to CNN and Fox News, and perform paired analyses to control for time. Across methods, the results converge on a clear pattern: post-purchase, Sinclair-owned stations increasingly cover national/political topics, with a rise in politicized language and greater similarity to polarized national outlets, while traditional local topics decline. The findings imply a gradual erosion of community-focused local news and highlight YouTube transcripts as a valuable data source for monitoring content shifts in broadcast media.

Abstract

Local news stations are often considered to be reliable sources of non-politicized information, particularly local concerns that residents care about. Because these stations are trusted news sources, viewers are particularly susceptible to the information they report. The Sinclair Broadcast group is a broadcasting company that has acquired many local news stations in the last decade. We investigate the effects of local news stations being acquired by Sinclair: how does coverage change? We use computational methods to investigate changes in internet content put out by local news stations before and after being acquired by Sinclair and in comparison to national news outlets. We find that there is clear evidence that local news stations report more frequently on national news at the expense of local topics, and that their coverage of polarizing national topics increases.

Figures (12)

• Figure 1: The distribution of the data by year. Vertical lines denote the date that the station was purchased by Sinclair.
• Figure 2: Results for STM on all, 2014, 2015, and 2016 data subsets. Change in topic proportion shifting from CNN to Fox on the x-axis and before Sinclair purchase to after Sinclair purchase on the y-axis. Coverage becomes more national and political in stations purchased by Sinclair, with stations before purchase discussing local topics.
• Figure 3: Comparing embedding similarity for our target words to embeddings for CNN and Fox News between the years 2014-2016. Arrows show the shift for embeddings trained on data before acquisition to embeddings trained on data after acquisition. There is a clear trend towards increasing nationalization-- similarity tends to increase to both national news outlets.
• Figure 4: Results for STM on paired data before 2020. Change in topic proportion shifting from non-Sinclair to Sinclair affiliate on the x-axis, and shift before and after purchase date is shown with arrows. Red denotes national topics and blue denotes local topics. Topic list is shown on the y-axis. Topics with unclear national/local interpretation are omitted here, and included in Figure \ref{['fig:paired-pre2020-appendix']}.
• Figure 5: Results for STM on all data. Change in topic proportion shifting from CNN to Fox on the x-axis and before Sinclair purchase to after Sinclair purchase on the y-axis. Topics 10 (cooking), 26 (family), and 24 (station 2) are omitted, but can be found in Figure \ref{['fig:stm-all-main']}.