Text & Content Analysis

Context: entity (trains)  |  Window: 24h · 7d · 30d  |  Corpus: 1 articles

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
Politics Sports Business Technology Science Health Entertainment

Corpus KPIs

Entity
trains
Window
Last 24h
Articles
1
From
2026-08-07 06:32:44+00
To
2026-08-07 06:32:44+00
Range
2026-08-07 05:49:56.998246+00 → 2026-08-08 05:49:56.998246+00
Who’s being talked about

Top Entities

Entity Label Mentions Actions
chris wright PERSON 1 📊 🔍 🧲
edt rail ORG 1 📊 🔍 🧲
england GPE 1 📊 🔍 🧲
midlands PERSON 1 📊 🔍 🧲
network rail ORG 1 📊 🔍 🧲
network rails ORG 1 📊 🔍 🧲
north west GPE 1 📊 🔍 🧲
read more share updated WORK_OF_ART 1 📊 🔍 🧲
trains PERSON 1 📊 🔍 🧲
Who’s talking

Top Sources (Domains)

Domain Articles % Actions
theguardian.com 1 100.00 📊 📰 🧲
How the stories are being framed

Top Narrative Frames

Frame Weight Actions
Environment, Climate 0.4700 📊 🧲
Technology 0.4300 📊 🧲
Health 0.0900 📊 🧲
How it feels

Sentiment

Label Articles Actions
😐 Neutral 1 📊 🧲

Articles included

Top entities
Top sources
Top narrative frames
Pub Date Category Domain Title Analyze Author Sent Score
2026-08-07 06:32:44+00 Business theguardian.com Rail passengers facing more disruption after power outage; UK house prices stagnate Analyze https://www.theguardian.com/profile/graemewearden 😐 neutral 0.1476