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
bluesky share
Articles
14
From
2026-08-19 10:00:59+00
To
2026-09-13 21:36:52+00
Range
2026-08-19 01:12:07.798081+00 →
2026-09-18 01:12:07.798081+00
Who’s being talked about
Top Entities
| Entity | Label | Mentions | Actions |
|---|---|---|---|
| bluesky share | PERSON | 14 | 📊 🔍 🧲 |
| facebook share on bluesky opens | WORK_OF_ART | 11 | 📊 🔍 🧲 |
| trinity audio | ORG | 11 | 📊 🔍 🧲 |
| donald trump | PERSON | 7 | 📊 🔍 🧲 |
| threads share | PERSON | 7 | 📊 🔍 🧲 |
| ct | ORG | 6 | 📊 🔍 🧲 |
| opens | ORG | 6 | 📊 🔍 🧲 |
| print email | PERSON | 6 | 📊 🔍 🧲 |
| connecticut | GPE | 5 | 📊 🔍 🧲 |
| chicago | GPE | 4 | 📊 🔍 🧲 |
| new york | GPE | 4 | 📊 🔍 🧲 |
| uconn | GPE | 4 | 📊 🔍 🧲 |
| american | NORP | 3 | 📊 🔍 🧲 |
| canada | GPE | 3 | 📊 🔍 🧲 |
| cdt getting | ORG | 3 | 📊 🔍 🧲 |
| chicago tribune | ORG | 3 | 📊 🔍 🧲 |
| hartford courant | PERSON | 3 | 📊 🔍 🧲 |
| kevin rennie | PERSON | 3 | 📊 🔍 🧲 |
| ned lamont | PERSON | 3 | 📊 🔍 🧲 |
| one | CARDINAL | 3 | 📊 🔍 🧲 |
| state | ORG | 3 | 📊 🔍 🧲 |
| africa | LOC | 2 | 📊 🔍 🧲 |
| ai | ORG | 2 | 📊 🔍 🧲 |
| aim | PERSON | 2 | 📊 🔍 🧲 |
Who’s talking
Top Sources (Domains)
| Domain | Articles | % | Actions |
|---|---|---|---|
|
|
6 | 42.86 | 📊 📰 🧲 |
|
|
4 | 28.57 | 📊 📰 🧲 |
|
|
2 | 14.29 | 📊 📰 🧲 |
|
|
1 | 7.14 | 📊 📰 🧲 |
|
|
1 | 7.14 | 📊 📰 🧲 |
How the stories are being framed
Top Narrative Frames
| Frame | Weight | Actions |
|---|---|---|
| Government | 3.1300 | 📊 🧲 |
| Business, Companies | 2.6700 | 📊 🧲 |
| Technology | 2.4700 | 📊 🧲 |
| Environment, Climate | 2.0000 | 📊 🧲 |
| Civil Unrest, Conflict | 0.8600 | 📊 🧲 |
| Health | 0.7800 | 📊 🧲 |
| Entertainment | 0.7500 | 📊 🧲 |
| Friends and Family | 0.7200 | 📊 🧲 |
| Other | 0.5400 | — |
Articles included
Top entities
Top sources
Top narrative frames