Source profile
The Guardian
✓Mainstream reporting with emphasis on policy, privacy, and society. Good for tech regulation and consumer impact stories. Often covers platform governance and digital rights. Useful for UK/EU angles and broader context.
Official source: NoMainstream media: YesLast activity: 5h ago
20 items analyzedVisit site ↗
Insights Metrics v2
Metric board
Publisher typeWhether the publisher is an official company channel or a mainstream outlet. Best-effort editorial judgements, hand-set per source.
24h
mainstream
Sample: 38Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
7d
mainstream
Sample: 192Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
30d
mainstream
Sample: 874Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
Articles publishedThe number of final articles from this source whose event date falls in the window, with the change from the previous window. Counts what we collected; sources run on different schedules.
24h
38
Sample: 38Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
7d
192was 195
▼ 2% (corpus -10%)
Sample: 192Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
30d
874was 42
▲ 1981% (corpus +38%)
Sample: 874Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
Active daysThe number of days in the window with at least one final article from this source. For sources that rarely expose a publish date, this is based on collection date.
24h
- Active days
- 1
- Dated share
- 97.4%
Sample: 38Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
7d
- Active days
- 7
- Dated share
- 99.0%
Sample: 192Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
30d
- Active days
- 30
- Dated share
- 99.1%
Sample: 874Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
Topic mixThe five categories that appear most often in the source's final articles. Same generous multi-labelling as E7.
24h
Not enough data
not offered for this window
7d
Business35%
Regulation31%
AI25%
Security16%
Entertainment Industry Tech7%
Sample: 192Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
30d
Business45%
Regulation31%
AI24%
Security15%
Entertainment Industry Tech8%
Sample: 874Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
Content-type mixWhat kind of pieces the source publishes. Coarse AI labels - labelled 'AI-classified article type'.
24h
Not enough data
not offered for this window
7d
News reporting77%
Breaking news6%
Announcement6%
Untyped6%
Analysis3%
Other3%
Sample: 192Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
30d
News reporting75%
Untyped7%
Announcement6%
Analysis6%
Breaking news5%
Other2%
Sample: 874Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
Tone mix and net toneThe distribution of article-level sentiment in the source's final articles, plus net tone. Official channels are self-promotional by nature.
24h
Not enough data
not offered for this window
7d
Negative57%
Mixed20%
Positive15%
Neutral8%
Net tone: Negative · -0.42
Sample: 131Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
30d
Negative53%
Mixed19%
Positive16%
Neutral12%
Net tone: Negative · -0.37
Sample: 684Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
Most-covered entitiesThe top 5 linked entities in the source's final articles. Catalog gaps and disabled forms under-count.
24h
Not enough data
not offered for this window
7d
OpenAI6%
Alphabet2%
Apple2%
Elon Musk2%
Palantir2%
Sample: 192Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
30d
OpenAI5%
Anthropic2%
Alphabet1%
Apple1%
Elon Musk1%
Sample: 874Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
Regional focusWhich parts of the world this source's coverage concerns. The AI's reading of the article's geography, not the outlet's country of registration.
24h
Not enough data
not offered for this window
7d
Global 10.9% · Unspecified 10.9%
US64%
UK12%
EU9%
Sample: 151Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
30d
Global 17.5% · Unspecified 7.6%
US64%
UK16%
EU11%
Sample: 662Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
Audiences coveredWhich audiences this source's articles say are affected. Consumers is the corpus default; read every number as a deviation from it.
24h
Not enough data
not offered for this window
7d
Consumers53%
Others35%
Governments31%
- Consumers+8.5pp vs baseline
- Others+9.4pp vs baseline
- Governments+19.1pp vs baseline
Sample: 192Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
30d
Consumers54%
Governments25%
Others25%
- Consumers+9.3pp vs baseline
- Governments+14.6pp vs baseline
- Others+6.1pp vs baseline
Sample: 874Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
Sourcing-strength mixHow often the AI judged an article's own sourcing to be strong versus thin, for this outlet's articles. The model's assessment of one article's sourcing, made without browsing. Never a publisher reliability or trust score, never used to rank sources.
24h
Not enough data
not offered for this window
7d
High81%
Medium15%
Low0%
Sample: 192Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
30d
High89%
Medium9%
Low0%
Sample: 874Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
Confidence mixHow sure the model was about its own reading of each article. Uncalibrated self-confidence, descriptive only.
24h
Not enough data
not offered for this window
7d
High55%
Medium40%
Low2%
Sample: 192Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
30d
High56%
Medium41%
Low1%
Sample: 874Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
Stance profileWhere the stories sit in a trend's life - accelerating, mature, or an early signal. An AI reading of the article's framing, not a market judgement.
24h
Not enough data
not offered for this window
7d
Accelerating64%
Mature18%
Early signal15%
Other0%
Sample: 192Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
30d
Accelerating67%
Mature19%
Early signal13%
Other0%
Sample: 874Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
Event types coveredWhich kinds of events this outlet reports on. Same 2026-08-10 start date and New-Product skew as E12.
24h
Not enough data
not offered for this window
7d
Not enough data
not enough data (9 of 20)
30d
75 rated (8.6% of coverage)
New Product32%
Lawsuit31%
Partnership9%
Personnel Change8%
Security Vulnerability8%
Sample: 75Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
Evidence-basis mixHow much of this outlet's coverage is built on official confirmation versus rumor, anonymous sourcing, or opinion. Correlated with the outlet's beat, never used as a trust ranking.
24h
Not enough data
not offered for this window
7d
169 rated (88.0% of coverage)
On record sources56%
Official announcement39%
Opinion5%
Anonymous sources1%
Sample: 169Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
30d
514 rated (58.8% of coverage)
On record sources51%
Official announcement40%
Opinion8%
Analyst estimate0%
Anonymous sources0%
Sample: 514Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
Story-phase mixWhether this outlet mostly breaks stories first or mostly follows up, reacts, and explains. Orthogonal to S5's content-type mix by prompt design.
24h
Not enough data
not offered for this window
7d
173 rated (90.1% of coverage)
First report97%
Reaction or analysis2%
Follow up1%
Sample: 173Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
30d
525 rated (60.1% of coverage)
First report95%
Reaction or analysis4%
Follow up1%
Explainer or recap0%
Sample: 525Sample size — how many underlying data points (e.g. labeled mentions, rated articles, or statements) this metric was actually computed from. Can be smaller than the entity or source's total coverage count.
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