Text & Content Analysis

Context: entity (berlin)  |  Window: 24h Β· 7d Β· 30d  |  Corpus: 3 articles

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.

Corpus KPIs

Entity
berlin
Window
Last 30 days
Articles
3
From
2026-04-06 15:26:04+00
To
2026-04-28 11:37:20+00
Range
2026-03-29 21:04:51.842146+00 β†’ 2026-04-28 21:04:51.842146+00
How the stories are being framed

Top Narrative Frames

Frame Weight Actions
Government 0.8100 πŸ“Š 🧲
Business, Companies 0.6100 πŸ“Š 🧲
Civil Unrest, Conflict 0.4600 πŸ“Š 🧲
Technology 0.3800 πŸ“Š 🧲
Political Theatre 0.2700 πŸ“Š 🧲
Environment, Climate 0.2700 πŸ“Š 🧲
Food and Beverage 0.1100 πŸ“Š 🧲
Health 0.0900 πŸ“Š 🧲
How it feels

Sentiment

Label Articles Actions
😐 Neutral 3 πŸ“Š 🧲

Articles included

Top entities
Top sources
Top narrative frames
Pub Date Category Domain Title Analyze Author Sent Score
2026-04-28 11:37:20+00 Business fortune.com How a Spanish startup pivoted to video AI and built a $230 million ARR business with no VC funding Analyze Alexei Oreskovic 😐 neutral 0.0198
2026-04-14 15:02:48+00 Politics dw.com Germany's aid to Ukraine faces challenges Analyze Christoph Hasselbach 😐 neutral 0.0916
2026-04-06 15:26:04+00 Politics theweek.com β€˜Long after that debt is paid, we keep sending the bill’ Analyze https://theweek.com/author/justin-klawans 😐 neutral 0.216