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
berlin
Articles
7
From
2026-08-18 11:00:00+00
To
2026-09-14 03:00:00+00
Range
2026-08-15 06:35:54.390423+00 →
2026-09-14 06:35:54.390423+00
Who’s being talked about
Top Entities
| Entity | Label | Mentions | Actions |
|---|---|---|---|
| berlin | GPE | 7 | 📊 🔍 🧲 |
| germany | GPE | 4 | 📊 🔍 🧲 |
| u.s. | GPE | 4 | 📊 🔍 🧲 |
| afd | ORG | 2 | 📊 🔍 🧲 |
| american | NORP | 2 | 📊 🔍 🧲 |
| britain | GPE | 2 | 📊 🔍 🧲 |
| email print copy | PERSON | 2 | 📊 🔍 🧲 |
| german | NORP | 2 | 📊 🔍 🧲 |
| germans | NORP | 2 | 📊 🔍 🧲 |
| guardian | ORG | 2 | 📊 🔍 🧲 |
| javascript | PRODUCT | 2 | 📊 🔍 🧲 |
| nazi | NORP | 2 | 📊 🔍 🧲 |
| nazis | NORP | 2 | 📊 🔍 🧲 |
| saxonyanhalt | ORG | 2 | 📊 🔍 🧲 |
| share prefer | PERSON | 2 | 📊 🔍 🧲 |
| share reuse | PERSON | 2 | 📊 🔍 🧲 |
| spd | ORG | 2 | 📊 🔍 🧲 |
| two decades later | DATE | 2 | 📊 🔍 🧲 |
| 116 billion | MONEY | 1 | 📊 🔍 🧲 |
| 2 million | MONEY | 1 | 📊 🔍 🧲 |
| a few years later | DATE | 1 | 📊 🔍 🧲 |
| aberdeen | GPE | 1 | 📊 🔍 🧲 |
| adolf hitlers | PERSON | 1 | 📊 🔍 🧲 |
| africa | LOC | 1 | 📊 🔍 🧲 |
| african | NORP | 1 | 📊 🔍 🧲 |
Who’s talking
Top Sources (Domains)
| Domain | Articles | % | Actions |
|---|---|---|---|
|
|
2 | 28.57 | 📊 📰 🧲 |
|
|
1 | 14.29 | 📊 📰 🧲 |
|
|
1 | 14.29 | 📊 📰 🧲 |
|
|
1 | 14.29 | 📊 📰 🧲 |
|
|
1 | 14.29 | 📊 📰 🧲 |
|
|
1 | 14.29 | 📊 📰 🧲 |
How the stories are being framed
Top Narrative Frames
| Frame | Weight | Actions |
|---|---|---|
| Business, Companies | 3.3100 | 📊 🧲 |
| Civil Unrest, Conflict | 0.8900 | 📊 🧲 |
| Government | 0.7600 | 📊 🧲 |
| Entertainment | 0.7100 | 📊 🧲 |
| Environment, Climate | 0.6000 | 📊 🧲 |
| Political Theatre | 0.2400 | 📊 🧲 |
| Food and Beverage | 0.1700 | 📊 🧲 |
| Friends and Family | 0.1400 | 📊 🧲 |
| Other | 0.1500 | — |
Articles included
Top entities
Top sources
Top narrative frames