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
claude
Articles
11
From
2026-04-06 09:11:01+00
To
2026-05-01 08:26:38+00
Range
2026-04-03 21:32:03.255475+00 →
2026-05-03 21:32:03.255475+00
Who’s being talked about
Top Entities
| Entity | Label | Mentions | Actions |
|---|---|---|---|
| claude | PRODUCT | 11 | 📊 🔍 🧲 |
| ai | ORG | 7 | 📊 🔍 🧲 |
| one | CARDINAL | 3 | 📊 🔍 🧲 |
| american | NORP | 2 | 📊 🔍 🧲 |
| ORG | 2 | 📊 🔍 🧲 | |
| lions | ORG | 2 | 📊 🔍 🧲 |
| meta | ORG | 2 | 📊 🔍 🧲 |
| microsoft | ORG | 2 | 📊 🔍 🧲 |
| openai | PERSON | 2 | 📊 🔍 🧲 |
| san antonio | GPE | 2 | 📊 🔍 🧲 |
| texans | NORP | 2 | 📊 🔍 🧲 |
| texas | GPE | 2 | 📊 🔍 🧲 |
| u.s. | GPE | 2 | 📊 🔍 🧲 |
| utc | ORG | 2 | 📊 🔍 🧲 |
| yahoo sports | ORG | 2 | 📊 🔍 🧲 |
| yahoo sports staff | ORG | 2 | 📊 🔍 🧲 |
| 18 billion | MONEY | 1 | 📊 🔍 🧲 |
| 85 billion | MONEY | 1 | 📊 🔍 🧲 |
| abc | ORG | 1 | 📊 🔍 🧲 |
| about twothirds | CARDINAL | 1 | 📊 🔍 🧲 |
| accuracy questions | PERSON | 1 | 📊 🔍 🧲 |
| accuracy users | PERSON | 1 | 📊 🔍 🧲 |
| agrawal | PRODUCT | 1 | 📊 🔍 🧲 |
| ai emerging technology | ORG | 1 | 📊 🔍 🧲 |
| albus | GPE | 1 | 📊 🔍 🧲 |
How the stories are being framed
Top Narrative Frames
| Frame | Weight | Actions |
|---|---|---|
| Business, Companies | 3.6700 | 📊 🧲 |
| Environment, Climate | 2.4700 | 📊 🧲 |
| Government | 2.1900 | 📊 🧲 |
| Technology | 1.0800 | 📊 🧲 |
| Friends and Family | 0.5700 | 📊 🧲 |
| Health | 0.4300 | 📊 🧲 |
| Civil Unrest, Conflict | 0.2600 | 📊 🧲 |
| Entertainment | 0.1800 | 📊 🧲 |
| Other | 0.0200 | — |
Articles included
Top entities
Top sources
Top narrative frames