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
mit
Articles
9
From
2026-06-30 11:15:56+00
To
2026-07-24 15:36:22+00
Range
2026-06-29 02:13:31.200188+00 →
2026-07-29 02:13:31.200188+00
Who’s being talked about
Top Entities
| Entity | Label | Mentions | Actions |
|---|---|---|---|
| mit | ORG | 9 | 📊 🔍 🧲 |
| u.s. | GPE | 6 | 📊 🔍 🧲 |
| ai | ORG | 5 | 📊 🔍 🧲 |
| china | GPE | 5 | 📊 🔍 🧲 |
| americans | NORP | 2 | 📊 🔍 🧲 |
| chinese | NORP | 2 | 📊 🔍 🧲 |
| facebook x reddit pinterest | ORG | 2 | 📊 🔍 🧲 |
| future | ORG | 2 | 📊 🔍 🧲 |
| get | NORP | 2 | 📊 🔍 🧲 |
| google newsletter subscribe | ORG | 2 | 📊 🔍 🧲 |
| harvard | ORG | 2 | 📊 🔍 🧲 |
| k | NORP | 2 | 📊 🔍 🧲 |
| live science | ORG | 2 | 📊 🔍 🧲 |
| logout read | PERSON | 2 | 📊 🔍 🧲 |
| please | ORG | 2 | 📊 🔍 🧲 |
| privacy policy | PERSON | 2 | 📊 🔍 🧲 |
| scientists | NORP | 2 | 📊 🔍 🧲 |
| stanford | ORG | 2 | 📊 🔍 🧲 |
| stories | ORG | 2 | 📊 🔍 🧲 |
| 124 trillion | MONEY | 1 | 📊 🔍 🧲 |
| a b | PERSON | 1 | 📊 🔍 🧲 |
| abc | ORG | 1 | 📊 🔍 🧲 |
| abhishek lodha | PERSON | 1 | 📊 🔍 🧲 |
| advent | PERSON | 1 | 📊 🔍 🧲 |
How the stories are being framed
Top Narrative Frames
| Frame | Weight | Actions |
|---|---|---|
| Technology | 2.2600 | 📊 🧲 |
| Business, Companies | 2.0500 | 📊 🧲 |
| Government | 2.0300 | 📊 🧲 |
| Environment, Climate | 1.3000 | 📊 🧲 |
| Friends and Family | 0.6200 | 📊 🧲 |
| Political Theatre | 0.3600 | 📊 🧲 |
| Health | 0.1800 | 📊 🧲 |
| Food and Beverage | 0.1200 | 📊 🧲 |
| Other | 0.0100 | — |
Articles included
Top entities
Top sources
Top narrative frames