Reverse mortgage professionals react to resignation of HUD Secretary Fudge - HousingWire
- Bias Rating
-10% Center
- Reliability
55% ReliableFair
- Policy Leaning
2% Center
- Politician Portrayal
44% Positive
Extremely
Liberal
Very
Liberal
Moderately
Liberal
Somewhat Liberal
Center
Somewhat Conservative
Moderately
Conservative
Very
Conservative
Extremely
Conservative
-100%
Liberal
100%
Conservative
Continue For Free
Create your free account to see the in-depth bias analytics and more.
Continue
Continue
By creating an account, you agree to our Terms and Privacy Policy, and subscribe to email updates. Already a member: Log inBias 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
21% Positive
- Conservative
Sentence | Sentiment | Bias |
---|---|---|
"Scott Norman, a NRMLA co-chair and vice president at Finance of America Reverse (FAR), also thanked Fudge for her service." | Positive | 20% Conservative |
"In reflecting on Secretary Fudge's tenure, I am grateful for her steady support of the HECM program, Irwin said." | Positive | 32% Conservative |
"We applaud Secretary Fudge's efforts and thank her for the support she showed to the HECM industry throughout her time at HUD, Norman said." | Positive | 30% Conservative |
Upgrade your account to obtain complete site access and more analytics below. |
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% : "Scott Norman, a NRMLA co-chair and vice president at Finance of America Reverse (FAR), also thanked Fudge for her service.*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.