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
eu
Articles
9
From
2026-07-22 12:30:00+00
To
2026-07-29 08:14:20+00
Range
2026-07-22 11:19:08.368808+00 β
2026-07-29 11:19:08.368808+00
Whoβs being talked about
Top Entities
| Entity | Label | Mentions | Actions |
|---|---|---|---|
| eu | ORG | 9 | π π 𧲠|
| u.s. | GPE | 6 | π π 𧲠|
| europe | LOC | 4 | π π 𧲠|
| donald trump | ORG | 3 | π π 𧲠|
| russia | GPE | 3 | π π 𧲠|
| 1 billion | MONEY | 2 | π π 𧲠|
| ai | ORG | 2 | π π 𧲠|
| european | NORP | 2 | π π 𧲠|
| fda | ORG | 2 | π π 𧲠|
| france | GPE | 2 | π π 𧲠|
| ORG | 2 | π π 𧲠| |
| microsoft | ORG | 2 | π π 𧲠|
| spain | GPE | 2 | π π 𧲠|
| EVENT | 1 | π π 𧲠| |
| 11 | MONEY | 1 | π π 𧲠|
| 430 million | MONEY | 1 | π π 𧲠|
| 460 million | MONEY | 1 | π π 𧲠|
| 490 million | MONEY | 1 | π π 𧲠|
| 5247 million | MONEY | 1 | π π 𧲠|
| 890 million | MONEY | 1 | π π 𧲠|
| 90 billion | MONEY | 1 | π π 𧲠|
| against flutter entertainments | ORG | 1 | π π 𧲠|
| agency | ORG | 1 | π π 𧲠|
| ai companies or | ORG | 1 | π π 𧲠|
Whoβs talking
Top Sources (Domains)
| Domain | Articles | % | Actions |
|---|---|---|---|
|
|
1 | 11.11 | π π° 𧲠|
|
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1 | 11.11 | π π° 𧲠|
|
|
1 | 11.11 | π π° 𧲠|
|
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1 | 11.11 | π π° 𧲠|
|
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1 | 11.11 | π π° 𧲠|
|
|
1 | 11.11 | π π° 𧲠|
|
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1 | 11.11 | π π° 𧲠|
|
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1 | 11.11 | π π° 𧲠|
|
|
1 | 11.11 | π π° 𧲠|
How the stories are being framed
Top Narrative Frames
| Frame | Weight | Actions |
|---|---|---|
| Government | 2.3500 | π 𧲠|
| Technology | 2.1300 | π 𧲠|
| Business, Companies | 1.6600 | π 𧲠|
| Civil Unrest, Conflict | 1.1700 | π 𧲠|
| Environment, Climate | 0.8000 | π 𧲠|
| Political Theatre | 0.4200 | π 𧲠|
| Friends and Family | 0.2400 | π 𧲠|
| Health | 0.1700 | π 𧲠|
| Other | 0.0900 | β |
Articles included
Top entities
Top sources
Top narrative frames