
More Than 350,000 Virginians Voted Before They Knew Dem Candidate Endorsed Political Violence
- Bias Rating
- Reliability
35% ReliableAverage
- Policy Leaning
26% Somewhat Right
- Politician Portrayal
N/A
Continue For Free
Create your free account to see the in-depth bias analytics and more.
By creating an account, you agree to our Terms and Privacy Policy, and subscribe to email updates.
Bias Score Analysis
The A.I. bias rating includes policy and politician portrayal leanings based on the author’s tone found in the article using machine learning. 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.
Sentiments
-29% Negative
- Liberal
- Conservative
Sentence | Sentiment | Bias |
---|---|---|
Unlock this feature by upgrading to the Pro plan. |
Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
Extremely
Liberal
Very
Liberal
Moderately
Liberal
Somewhat Liberal
Center
Somewhat Conservative
Moderately
Conservative
Very
Conservative
Extremely
Conservative
-100%
Liberal
100%
Conservative

Contributing sentiments towards policy:
48% : Just two days before Jones' text messages endorsing political violence were made public, the Richmond-Times Dispatch revealed he had capitalized on a reckless driving charge by logging community service hours with his own political action committee (PAC), Meet Our Moment. 291,420 votes had already been cast by that point, more than double the 144,721 votes recorded at the same stage in the 2021 election.45% : According to Coyner, during a heated discussion about removing qualified immunity protections for officers, Jones suggested that the deaths of a few police officers might prevent them from killing civilians.
34% : Over 350,000 Virginians voted in the 2025 election prior to the news that Democratic Attorney General candidate Jay Jones had endorsed political violence, according to early voting data.
*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.