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
share prefer
Articles
1
From
2026-05-20 10:39:06+00
To
2026-05-20 10:39:06+00
Range
2026-05-19 22:43:38.133241+00 →
2026-05-20 22:43:38.133241+00
Who’s being talked about
Top Entities
| Entity | Label | Mentions | Actions |
|---|---|---|---|
| alamy life | ORG | 1 | 📊 🔍 🧲 |
| amelia | GPE | 1 | 📊 🔍 🧲 |
| at least 80 | PERCENT | 1 | 📊 🔍 🧲 |
| ball | PERSON | 1 | 📊 🔍 🧲 |
| biobank | ORG | 1 | 📊 🔍 🧲 |
| christopher ball | PERSON | 1 | 📊 🔍 🧲 |
| devi sridhar | PERSON | 1 | 📊 🔍 🧲 |
| edt | ORG | 1 | 📊 🔍 🧲 |
| google individuals | ORG | 1 | 📊 🔍 🧲 |
| guardian | ORG | 1 | 📊 🔍 🧲 |
| harvard th chan | ORG | 1 | 📊 🔍 🧲 |
| health health | ORG | 1 | 📊 🔍 🧲 |
| jay olshansky | PERSON | 1 | 📊 🔍 🧲 |
| leslie kenny | PERSON | 1 | 📊 🔍 🧲 |
| living longer | PERSON | 1 | 📊 🔍 🧲 |
| muir gray | PERSON | 1 | 📊 🔍 🧲 |
| nancy krieger | PERSON | 1 | 📊 🔍 🧲 |
| older people medical | ORG | 1 | 📊 🔍 🧲 |
| oxford | ORG | 1 | 📊 🔍 🧲 |
| oxford healthspan | PERSON | 1 | 📊 🔍 🧲 |
| oxford population health | ORG | 1 | 📊 🔍 🧲 |
| parachute | ORG | 1 | 📊 🔍 🧲 |
| paul chen | PERSON | 1 | 📊 🔍 🧲 |
| prof denis noble | PERSON | 1 | 📊 🔍 🧲 |
| share prefer | PERSON | 1 | 📊 🔍 🧲 |
Articles included
Top entities
Top sources
Top narrative frames
| Pub Date | Category | Domain | Title | Analyze | Author | Sent | Score |
|---|---|---|---|---|---|---|---|
| 2026-05-20 10:39:06+00 | Health |
|
At least 80% responsibility for ill health in old age down to individual, says study | Analyze | Amelia Hill | 😐 neutral | 0.0818 |