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
eight
Articles
9
From
2026-07-09 15:36:02+00
To
2026-08-07 19:45:22+00
Range
2026-07-09 13:44:40.738749+00 →
2026-08-08 13:44:40.738749+00
Who’s being talked about
Top Entities
| Entity | Label | Mentions | Actions |
|---|---|---|---|
| eight | CARDINAL | 9 | 📊 🔍 🧲 |
| democrats | NORP | 6 | 📊 🔍 🧲 |
| republicans | NORP | 5 | 📊 🔍 🧲 |
| u.s. | GPE | 4 | 📊 🔍 🧲 |
| email print copy | PERSON | 2 | 📊 🔍 🧲 |
| facebook twitter | PERSON | 2 | 📊 🔍 🧲 |
| fda | ORG | 2 | 📊 🔍 🧲 |
| four | CARDINAL | 2 | 📊 🔍 🧲 |
| ice | ORG | 2 | 📊 🔍 🧲 |
| indiana | GPE | 2 | 📊 🔍 🧲 |
| kevin trainor | PERSON | 2 | 📊 🔍 🧲 |
| los angeles | GPE | 2 | 📊 🔍 🧲 |
| new york | GPE | 2 | 📊 🔍 🧲 |
| save facebook twitter | PERSON | 2 | 📊 🔍 🧲 |
| senate | ORG | 2 | 📊 🔍 🧲 |
| two | CARDINAL | 2 | 📊 🔍 🧲 |
| PERSON | 2 | 📊 🔍 🧲 | |
| 114 million | MONEY | 1 | 📊 🔍 🧲 |
| 12m | MONEY | 1 | 📊 🔍 🧲 |
| 38 million | MONEY | 1 | 📊 🔍 🧲 |
| a | PERSON | 1 | 📊 🔍 🧲 |
| a2dd | ORG | 1 | 📊 🔍 🧲 |
| a6c764e | PRODUCT | 1 | 📊 🔍 🧲 |
Who’s talking
Top Sources (Domains)
| Domain | Articles | % | Actions |
|---|---|---|---|
|
|
1 | 11.11 | 📊 📰 🧲 |
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1 | 11.11 | 📊 📰 🧲 |
|
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1 | 11.11 | 📊 📰 🧲 |
|
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1 | 11.11 | 📊 📰 🧲 |
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1 | 11.11 | 📊 📰 🧲 |
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1 | 11.11 | 📊 📰 🧲 |
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1 | 11.11 | 📊 📰 🧲 |
|
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1 | 11.11 | 📊 📰 🧲 |
|
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1 | 11.11 | 📊 📰 🧲 |
How the stories are being framed
Top Narrative Frames
| Frame | Weight | Actions |
|---|---|---|
| Government | 3.6200 | 📊 🧲 |
| Technology | 1.5200 | 📊 🧲 |
| Civil Unrest, Conflict | 0.9700 | 📊 🧲 |
| Health | 0.7900 | 📊 🧲 |
| Friends and Family | 0.5400 | 📊 🧲 |
| Entertainment | 0.5100 | 📊 🧲 |
| Environment, Climate | 0.4100 | 📊 🧲 |
| Business, Companies | 0.3400 | 📊 🧲 |
| Other | 0.3300 | — |
Articles included
Top entities
Top sources
Top narrative frames