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Tucson Weekly
Media Bias Rating

Tucson Weekly, a trusted source of news and culture, offers a diverse range of content that includes politics, sports, entertainment, and more. Established in 1984, Tucson Weekly has been a vital part of the Tucson, Arizona community since its inception. Founded by Douglas Bithers & Mark Goehring, the publication sought to provide a voice for local issues and to deliver engaging, well-rounded journalism to its readers. Information regarding its current ownership can be found on the organization's official website or by contacting them directly. Known for its commitment to highlighting local events, arts, and political developments, Tucson Weekly continues to be a cornerstone of news and entertainment in the region, fostering a sense of community and informed dialogue among its readers.

Bias Meter
Computer A.I. Score
Help
Our A.I. media bias rating of Tucson Weekly shows what policies Tucson Weekly supports and opposes including Tucson Weekly's conservative and liberal leanings based on analysis of three hundred of articles scanned daily using the latest data science and artificial intelligence technologies.
Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral.

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Center

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Conservative

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-100%
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100%
Conservative

Fair Reliability

*Our bias meter rating uses data science including sentiment analysis, machine learning and our proprietary algorithm for determining biases in news articles. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative and 0% being neutral. The rating is an independent analysis and is not affiliated nor sponsored by the news source or any other organization.

Analyst Score
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Biasly’s analyst team evaluates politician twitter accounts, voting records, and statements made in the press to determine leanings. Our diverse analyst team includes equal representation from conservative, center, and liberal viewpoints on every article we rate.

The Analyst Bias Score is on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral.
Reliability
Source Analysis Score
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The Source Analysis Score focuses on assessing the quality of sources and quotes used including their number, lengths, uniqueness, and diversity.
Fact Analysis Score
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The Fact Analysis Score focuses more on the accuracy of claims, facts, and sources presented in the article and any hints of selection and omission bias.
Overall Reliability
Other
Policy Leanings
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Our policy leanings for Fox News show what policies Fox News is biased on based on the sentiment leanings found in their news articles.

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Moderately
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Somewhat Liberal

Center

Somewhat Conservative

Moderately
Conservative

Very
Conservative

Extremely
Conservative

-100%
Liberal

100%
Conservative

Fair Reliability

*Our bias meter rating uses data science including sentiment analysis, machine learning and our proprietary algorithm for determining biases in news articles. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative and 0% being neutral. The rating is an independent analysis and is not affiliated nor sponsored by the news source or any other organization.

Author Bias
Politician Portrayal

58% negative

News Source Ranking
Tucson Weekly is ranked 41,676 among other media sources and has an average of 43,374 monthly visits according to Similar Web.
At Biasly, we rate political news articles from Tucson Weekly using our Bias Meter technology to provide readers better insight into the conservative and liberal leanings present in today’s media. Here is a list of biases found in articles, political policies, and politician biases from Tucson Weekly:

Tucson Weekly Articles

Date

Article title

Bias rating

ACTIONS

Tucson Weekly Politician Portrayal

PoliticianSentiment
Ratings are based on recent news using data science and A.I. technology.