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
norway
Articles
6
From
Sat, Sep 5 β’ 9:18 PM EDT
To
Wed, Sep 30 β’ 4:35 AM EDT
Range
Tue, Sep 1 β’ 3:37 AM EDT β
Thu, Oct 1 β’ 3:37 AM EDT
Whoβs being talked about
Top Entities
| Entity | Label | Mentions | Actions |
|---|---|---|---|
| norway | GPE | 6 | π π 𧲠|
| norwegian | NORP | 3 | π π 𧲠|
| u.s. | GPE | 3 | π π 𧲠|
| donald trump | ORG | 2 | π π 𧲠|
| europe | LOC | 2 | π π 𧲠|
| european | NORP | 2 | π π 𧲠|
| kyiv | PERSON | 2 | π π 𧲠|
| moscow | GPE | 2 | π π 𧲠|
| portugal | GPE | 2 | π π 𧲠|
| russia | GPE | 2 | π π 𧲠|
| russian | NORP | 2 | π π 𧲠|
| spain | GPE | 2 | π π 𧲠|
| spanish | NORP | 2 | π π 𧲠|
| ukraine | GPE | 2 | π π 𧲠|
| ukrainian | NORP | 2 | π π 𧲠|
| ukrainians | NORP | 2 | π π 𧲠|
| volodymyr zelensky | PERSON | 2 | π π 𧲠|
| zelensky | PERSON | 2 | π π 𧲠|
| academy | ORG | 1 | π π 𧲠|
| activeduty personnel by | PRODUCT | 1 | π π 𧲠|
| adam escada | PERSON | 1 | π π 𧲠|
| alps | LOC | 1 | π π 𧲠|
| amazon | ORG | 1 | π π 𧲠|
| america | GPE | 1 | π π 𧲠|
| american | NORP | 1 | π π 𧲠|
Whoβs talking
Top Sources (Domains)
| Domain | Articles | % | Actions |
|---|---|---|---|
|
|
2 | 33.33 | π π° 𧲠|
|
|
1 | 16.67 | π π° 𧲠|
|
|
1 | 16.67 | π π° 𧲠|
|
|
1 | 16.67 | π π° 𧲠|
|
|
1 | 16.67 | π π° 𧲠|
How the stories are being framed
Top Narrative Frames
| Frame | Weight | Actions |
|---|---|---|
| Business, Companies | 1.5600 | π 𧲠|
| Technology | 1.3200 | π 𧲠|
| Civil Unrest, Conflict | 0.9800 | π 𧲠|
| Political Theatre | 0.6600 | π 𧲠|
| Environment, Climate | 0.3900 | π 𧲠|
| Government | 0.3800 | π 𧲠|
| Food and Beverage | 0.2200 | π 𧲠|
| Friends and Family | 0.2200 | π 𧲠|
| Other | 0.2000 | β |
Articles included
Top entities
Top sources
Top narrative frames