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How people follow and judge local news

Source reportMethodology

Overview

Local news use appears softer than five years ago, but adults are not rejecting local TV news outright.

About 33% say they watch less local news than they did five years ago, compared with 26% who say more and 31% who say the same. Local TV news trust is mostly partial: 54% say they sometimes trust their local TV news networks.

Stacked breakdown

33% say they watch less local news than five years ago.

Thinking about local news, are you watching more, less or the same amount as you did 5 years ago?

More
25.7%
Less
32.5%
Same
30.8%
Don't watch local news
11.1%

2025 · base n 1,000 · +/- 3.2%

A

View source data

Less local news viewing outweighs more viewing

Asked about local news compared with five years ago, 33% say they watch less.

Another 31% say they watch the same amount, 26% say they watch more, and 11% say they do not watch local news.

Stacked breakdown

54% say they sometimes trust local TV news networks.

How often do you trust your local TV news networks?

I always trust them
17.0%
I sometimes trust them
53.7%
I rarely trust them
16.9%
I never trust them
3.6%
I don't watch local TV news
8.7%

2025 · base n 1,000 · +/- 3.2%

B

View source data

Trust in local TV news is mostly conditional

About 54% say they sometimes trust their local TV news networks. Another 17% say they always trust them.

Outright distrust is smaller: 17% rarely trust local TV news and 4% never trust it.

Stacked breakdown

76% say they used mostly Google to search for information online.

In the past 30 days, which tool have you used more often to search for information online?

Mostly Google Search
75.5%
Mostly ChatGPT
5.8%
I have used Google search and ChatGPT about the same
13.4%
I haven’t used either
5.3%

2025 · base n 1,000 · +/- 3.2%

A

View source data

Google still dominates online information search

Familiarity with major news brands remains high: 87% have heard of the New York Times, 84% the Wall Street Journal, and 72% the BBC.

For online search, 76% say they used mostly Google in the past 30 days, while 6% say mostly ChatGPT and 13% say they used both about the same.

Methodology

Full methodology
Mode
Verasight panel recruited via random address-based sampling, random person-to-person text messaging, and dynamic online targeting
Population
United States adults
Field dates
2025-08-01 → 2025-08-06
Base (unweighted)
1,000
Margin of error
+/- 3.2%
Module
A
Sponsor
Verasight
Weight variable
weight
Weighting targets
age, race/ethnicity, sex, income, education, region, metropolitan status

Sources

[4]
  • 01
    Thinking about local news, are you watching more, less or the same amount as you did 5 years ago?Anchors the topic in changed local news viewing habits.reports.verasight.io/reports/verasight-quirks-omnibus-survey
  • 02
    How often do you trust your local TV news networks?Adds the trust measure for local TV news.reports.verasight.io/reports/verasight-quirks-omnibus-survey
  • 03
    Which of the following news media outlets, if any, have you heard of?Adds broader news-brand familiarity for national and international outlets.reports.verasight.io/reports/verasight-quirks-omnibus-survey
  • 04
    In the past 30 days, which tool have you used more often to search for information online?Adds an information-search context where Google remains far ahead of ChatGPT.reports.verasight.io/reports/verasight-quirks-omnibus-survey

Citation

Verasight Quirks Omnibus Survey, fielded August 1-6, 2025, N=1,000 United States adults, +/- 3.2%.

https://reports.verasight.io/reports/verasight-quirks-omnibus-survey#thinking-about-local-news-are-you-watching-more-less-or-the-same-amount-as-you-did-5-years-ago

Verasight survey methodology

How Verasight conducts surveys.

This page describes the Verasight general survey contract, separate from how the Data Library packages it. Each wave's specific field dates, sample sizes, and module breakdown are listed in that wave's report.

Mode
Verasight panel recruited via random address-based sampling, random person-to-person text messaging, and dynamic online targeting.
Population
US adults age 18+.
Sample design
Surveys are run as omnibus or single-topic waves. Omnibus waves are split into modules with their own respondent set, typically around one thousand respondents per module.
Field window
Each wave specifies its own field dates. Most omnibus waves field across roughly two weeks.
Weighting
Per-module weighting to CPS targets including age, race and ethnicity, sex, income, education, region, and metropolitan status.
Partisanship benchmark
Pew Research Center's NPORS benchmarking surveys, three-year running average.
Vote benchmark
2024 presidential vote population benchmarks.
Margin of error
Typically about plus or minus 3.4 to 3.6 percent per module at standard module sizes. Question-level MoE is recomputed when a base shrinks materially below the module baseline.
Reporting
Every wave is published as a standalone report at verasight.io/reports with full instrument and methodology.
Transparency
AAPOR transparency standards.

Wave-specific methodology, full weighting variable lists, and verbatim instrument text live in each report at verasight.io/reports.