
What College Football Playoff Committee Said About No. 5 Texas Longhorns
- Bias Rating
- Reliability
60% ReliableAverage
- Policy Leaning
-28% Somewhat Left
- 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
10% Positive
- Liberal
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:
60% : " The Longhorns took down then-No. 10 Michigan 31-12 in Ann Arbor on Sept. 7, a win that, at the time, was seen as a resume-boosting victory over the defending national champions.53% : AUSTIN -- The first College Football Playoff rankings were released Tuesday and the Texas Longhorns slid in at No. 5 while earning the No. 6 seed in the projected 12-team bracket.
52% : Texas proceeded to easily handle then-No. 18 Oklahoma 34-3 on Oct. 19 for another win over a ranked opponent, but the Sooners have stumbled their way to a 1-4 record in SEC play and are now fighting for bowl contention with three games left this season.
50% : One could argue that Texas' best win came on the road against then-No. 25 Vanderbilt on Oct. 26 after the team failed to secure a potential resume-defining victory in the 30-15 loss to Georgia a week prior.
*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.