Text & Content Analysis
This page analyzes how a selected category, entity, or narrative frame appears in recent news coverage within the specified time window. Metrics and breakdowns are derived from the active article corpus.
Explore by Category
Corpus KPIs
Entity
bill
Articles
15
From
2026-04-04 18:01:00+00
To
2026-04-29 08:00:50+00
Range
2026-04-03 07:10:58.326194+00 →
2026-05-03 07:10:58.326194+00
Who’s being talked about
Top Entities
| Entity | Label | Mentions | Actions |
|---|---|---|---|
| bill | PERSON | 15 | 📊 🔍 🧲 |
| house | ORG | 10 | 📊 🔍 🧲 |
| republicans | NORP | 10 | 📊 🔍 🧲 |
| senate | ORG | 7 | 📊 🔍 🧲 |
| u.s. | GPE | 6 | 📊 🔍 🧲 |
| colorado | GPE | 5 | 📊 🔍 🧲 |
| democrats | NORP | 5 | 📊 🔍 🧲 |
| marianne goodland | ORG | 5 | 📊 🔍 🧲 |
| marissa ventrelli | PERSON | 5 | 📊 🔍 🧲 |
| connecticut | GPE | 4 | 📊 🔍 🧲 |
| democrat | NORP | 4 | 📊 🔍 🧲 |
| washington | GPE | 4 | 📊 🔍 🧲 |
| 468 billion | MONEY | 3 | 📊 🔍 🧲 |
| colorado politics | PERSON | 3 | 📊 🔍 🧲 |
| ct mirror | ORG | 3 | 📊 🔍 🧲 |
| dc | GPE | 3 | 📊 🔍 🧲 |
| gop | ORG | 3 | 📊 🔍 🧲 |
| jeff hurd | PERSON | 3 | 📊 🔍 🧲 |
| one | CARDINAL | 3 | 📊 🔍 🧲 |
| paula noonan | PERSON | 3 | 📊 🔍 🧲 |
| second | ORDINAL | 3 | 📊 🔍 🧲 |
| today | DATE | 3 | 📊 🔍 🧲 |
| a few weeks ago | DATE | 2 | 📊 🔍 🧲 |
| alfred | ORG | 2 | 📊 🔍 🧲 |
Who’s talking
Top Sources (Domains)
| Domain | Articles | % | Actions |
|---|---|---|---|
|
|
5 | 33.33 | 📊 📰 🧲 |
|
|
3 | 20.00 | 📊 📰 🧲 |
|
|
2 | 13.33 | 📊 📰 🧲 |
|
|
1 | 6.67 | 📊 📰 🧲 |
|
|
1 | 6.67 | 📊 📰 🧲 |
|
|
1 | 6.67 | 📊 📰 🧲 |
|
|
1 | 6.67 | 📊 📰 🧲 |
|
|
1 | 6.67 | 📊 📰 🧲 |
How the stories are being framed
Top Narrative Frames
| Frame | Weight | Actions |
|---|---|---|
| Government | 7.6500 | 📊 🧲 |
| Business, Companies | 2.4800 | 📊 🧲 |
| Technology | 1.8700 | 📊 🧲 |
| Friends and Family | 1.2200 | 📊 🧲 |
| Environment, Climate | 1.0500 | 📊 🧲 |
| Civil Unrest, Conflict | 0.3200 | 📊 🧲 |
| Political Theatre | 0.1200 | 📊 🧲 |
| Entertainment | 0.1100 | 📊 🧲 |
| Other | 0.1200 | — |
Articles included
Top entities
Top sources
Top narrative frames