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
harvard university
Articles
8
From
2026-04-04 16:25:00+00
To
2026-05-03 14:29:36+00
Range
2026-04-04 00:57:37.888189+00 →
2026-05-04 00:57:37.888189+00
Who’s being talked about
Top Entities
| Entity | Label | Mentions | Actions |
|---|---|---|---|
| harvard university | ORG | 8 | 📊 🔍 🧲 |
| donald trump | PERSON | 7 | 📊 🔍 🧲 |
| u.s. | GPE | 7 | 📊 🔍 🧲 |
| uk | GPE | 3 | 📊 🔍 🧲 |
| washington | GPE | 3 | 📊 🔍 🧲 |
| ai | ORG | 2 | 📊 🔍 🧲 |
| american | NORP | 2 | 📊 🔍 🧲 |
| asia | LOC | 2 | 📊 🔍 🧲 |
| boston | GPE | 2 | 📊 🔍 🧲 |
| covid19 | ORG | 2 | 📊 🔍 🧲 |
| dc | GPE | 2 | 📊 🔍 🧲 |
| epa | ORG | 2 | 📊 🔍 🧲 |
| europe | LOC | 2 | 📊 🔍 🧲 |
| guardian | ORG | 2 | 📊 🔍 🧲 |
| paris | GPE | 2 | 📊 🔍 🧲 |
| tiktok | ORG | 2 | 📊 🔍 🧲 |
| un | ORG | 2 | 📊 🔍 🧲 |
| who | ORG | 2 | 📊 🔍 🧲 |
| PERSON | 1 | 📊 🔍 🧲 | |
| 5 million | MONEY | 1 | 📊 🔍 🧲 |
| 750 million | MONEY | 1 | 📊 🔍 🧲 |
| about a decade later | DATE | 1 | 📊 🔍 🧲 |
| advertisement sign | PERSON | 1 | 📊 🔍 🧲 |
Who’s talking
Top Sources (Domains)
| Domain | Articles | % | Actions |
|---|---|---|---|
|
|
1 | 12.50 | 📊 📰 🧲 |
|
|
1 | 12.50 | 📊 📰 🧲 |
|
|
1 | 12.50 | 📊 📰 🧲 |
|
|
1 | 12.50 | 📊 📰 🧲 |
|
|
1 | 12.50 | 📊 📰 🧲 |
|
|
1 | 12.50 | 📊 📰 🧲 |
|
|
1 | 12.50 | 📊 📰 🧲 |
|
|
1 | 12.50 | 📊 📰 🧲 |
How the stories are being framed
Top Narrative Frames
| Frame | Weight | Actions |
|---|---|---|
| Government | 2.0000 | 📊 🧲 |
| Business, Companies | 1.5400 | 📊 🧲 |
| Environment, Climate | 0.8400 | 📊 🧲 |
| Technology | 0.7500 | 📊 🧲 |
| Health | 0.7100 | 📊 🧲 |
| Friends and Family | 0.6200 | 📊 🧲 |
| Food and Beverage | 0.5600 | 📊 🧲 |
| Civil Unrest, Conflict | 0.5100 | 📊 🧲 |
| Other | 0.4200 | — |
Articles included
Top entities
Top sources
Top narrative frames