Podcast Publisher Bias

Particle API analyzes every well-classified podcast against a seven-point political bias scale, calibrated against a regional political framework (US, UK, EU, CANADA, AUSTRALIA, INDIA, or OTHER). The publisher-level endpoints described here roll those per-podcast verdicts up across every podcast a publisher controls, so advertisers, researchers, and platforms can reason about a publisher’s full footprint rather than evaluating shows one at a time.

Publisher-level bias intelligence is a Premium endpoint. The per-podcast bias rating remains available on the standard tier through GET /v1/podcasts//bias.

What the profile gives you

A bundle-buy decision (or a publisher-fit audit) needs more than the modal lean of a single show. Particle’s publisher bias profile captures the catalog along five dimensions:

Coverage (coverage block) — total_podcasts, analyzed_podcasts, and analyzed_coverage so callers know how much of the catalog the verdict draws from. Backfill is in flight; a value of coverage.analyzed_coverage materially below 1.0 means there are still un-analyzed shows.
Political content (political_content block) — political_content.share is the fraction of analyzed podcasts the agent rated as political (i.e. not NOT_POLITICAL). Distinguishes news-heavy publishers from entertainment-heavy publishers.
Lean (lean block, absent from the response when the publisher has no political content) — lean.avg_score on a –3 (extreme left) to +3 (extreme right) ordinal scale, restricted to political content.
Diversity — lean.stddev, the standard deviation of the lean across political podcasts. Low values indicate a monolithic publisher (e.g. The Daily Wire, MeidasTouch); high values indicate a heterogeneous catalog (iHeartPodcasts spans EXTREME_RIGHT to LEFT).
Distributions (distributions block) — bucket-level counts across the seven directional buckets plus NOT_POLITICAL, and a per-region breakdown by political_context so callers can audit the verdict directly.

The bias scale

Bucket	Score	Description
`EXTREME_LEFT`	–3	Far-left content with overt partisan framing.
`LEFT`	–2	Clearly left-leaning editorial perspective.
`LEANS_LEFT`	–1	Center-left orientation; mild partisan signal.
`CENTER`	0	Even-handed treatment of political topics.
`LEANS_RIGHT`	+1	Center-right orientation; mild partisan signal.
`RIGHT`	+2	Clearly right-leaning editorial perspective.
`EXTREME_RIGHT`	+3	Far-right content with overt partisan framing.
`NOT_POLITICAL`	—	Not substantively political content.

The numeric score is exposed so callers can sort, average, and visualize across podcasts; it is not a substitute for the literal bucket and NOT_POLITICAL content is excluded from score-based metrics.

Get a publisher’s bias profile

curl "https://api.particle.pro/v1/podcasts/publishers/iheartpodcasts/bias" \
  -H "X-API-Key: $PARTICLE_API_KEY"

const res = await fetch(
  "https://api.particle.pro/v1/podcasts/publishers/iheartpodcasts/bias",
  { headers: { "X-API-Key": process.env.PARTICLE_API_KEY } },
);
const profile = await res.json();

res = httpx.get(
    "https://api.particle.pro/v1/podcasts/publishers/iheartpodcasts/bias",
    headers={"X-API-Key": os.environ["PARTICLE_API_KEY"]},
)
profile = res.json()

Response

{
  "publisher": { "id": "...", "slug": "iheartpodcasts", "name": "iHeartPodcasts" },
  "coverage": {
    "total_podcasts": 210,
    "analyzed_podcasts": 85,
    "analyzed_coverage": 0.4048
  },
  "political_content": {
    "podcasts": 17,
    "share": 0.20,
    "avg_topic_percentage": 0.41
  },
  "lean": {                  // absent when political_content.podcasts == 0
    "avg_score": -0.47,
    "stddev": 1.62,
    "dominant_bias": "LEANS_LEFT"
  },
  "distributions": {
    "bias": [
      { "result": "NOT_POLITICAL", "count": 68 },
      { "result": "LEANS_LEFT", "count": 9 },
      { "result": "LEFT", "count": 4 },
      { "result": "RIGHT", "count": 3 },
      { "result": "EXTREME_RIGHT", "count": 1 }
    ],
    "region": [
      { "political_context": "UNKNOWN", "count": 68 },
      { "political_context": "US", "count": 17 }
    ]
  },
  "last_evaluated_at": "2026-04-12T18:33:21Z"
}

The response is intentionally grouped: coverage is “how much of the catalog the verdict draws from”, political_content is “how political the catalog is”, and lean is “where the political content sits on the ideological axis”. When a publisher has no political content at all (e.g. a sports-only network), the lean block is absent from the response — a single "lean" in obj check answers “is there a lean signal at all?”. Leaderboard entries share the same nested shape minus distributions.

List a publisher’s analyzed podcasts

Drill into the underlying podcasts that drove the profile. Filter by bias bucket(s) (comma-separated) or political_context, exclude NOT_POLITICAL podcasts, and sort by lean, recency, or name.

curl "https://api.particle.pro/v1/podcasts/publishers/npr/bias/podcasts?bias=LEFT,LEANS_LEFT&sort=lean_score&order=asc" \
  -H "X-API-Key: $PARTICLE_API_KEY"

Sort options:

Sort	Description
`lean_score`	-3..+3 ordinal lean. Default.
`evaluated_at`	Most recent analysis first (or oldest with `order=asc`).
`name`	Alphabetical.

Cross-publisher leaderboard

Rank publishers by a chosen bias metric. Useful for discovery (what are the most right-leaning podcast publishers in the US?) and reporting (which publishers are most catalog-diverse?). Score-based metrics gate small-sample publishers via min_analyzed_podcasts and min_political_podcasts.

curl "https://api.particle.pro/v1/podcasts/bias/publishers/leaderboard?metric=most_right_leaning&political_context=US&min_political_podcasts=5" \
  -H "X-API-Key: $PARTICLE_API_KEY"

Available metrics:

Metric	Description
`most_left_leaning`	Lowest `lean.avg_score` first. Requires ≥ `min_political_podcasts` political podcasts.
`most_right_leaning`	Highest `lean.avg_score` first. Requires ≥ `min_political_podcasts` political podcasts.
`most_political`	Highest `political_content.share` first. Distinguishes news publishers from entertainment publishers.
`most_diverse`	Highest `lean.stddev` first — publishers whose catalog spans a wide political range.
`most_monolithic`	Lowest `lean.stddev` first — publishers whose catalog is tightly clustered around one lean.
`most_analyzed`	Highest `coverage.analyzed_coverage` first — publishers whose catalog is closest to fully analyzed.

Flip view: which publishers carry the most podcasts in a given bias bucket?

The symmetric “given a bucket, which publishers?” lens. Useful when the question is “who carries the most RIGHT-leaning content?” rather than “where does publisher X stand?”.

curl "https://api.particle.pro/v1/podcasts/bias/RIGHT/publishers?sort=share&min_count=3" \
  -H "X-API-Key: $PARTICLE_API_KEY"

sort=count ranks by raw podcasts_in_bucket; sort=share ranks by podcasts_in_bucket / analyzed_podcasts. Use share to surface publishers whose catalog is concentrated in the bucket regardless of catalog size; count to surface the largest absolute footprints. Every entry includes up to five sample_podcast_ids so callers can spot-check the verdict without an extra request.

Methodology notes

Latest analysis only. Every aggregate is computed from the most recent non-deleted analysis per podcast (DISTINCT ON (podcast_id) ORDER BY evaluated_at DESC). Historical analyses are kept for audit but never contribute to the rolled-up profile.
NOT_POLITICAL is not 0. NOT_POLITICAL content is excluded from lean.avg_score, lean.stddev, and lean.dominant_bias. Including it as a CENTER proxy would silently muddy the lean signal for entertainment-heavy publishers.
Sample standard deviation. lean.stddev is the sample standard deviation (Bessel’s correction, n−1). It is null when there is fewer than two political podcasts.
Coverage caveat. Analysis backfill is in flight. Treat coverage.analyzed_coverage as a confidence proxy on the rolled-up verdict — publishers with low coverage should be re-checked once the backfill completes.

Getting started

Podcasts

Companies

Knowledge graph

Alerts

Errors

What the profile gives you

The bias scale

Get a publisher’s bias profile

List a publisher’s analyzed podcasts

Cross-publisher leaderboard

Flip view: which publishers carry the most podcasts in a given bias bucket?

Methodology notes

​What the profile gives you

​The bias scale

​Get a publisher’s bias profile

​List a publisher’s analyzed podcasts

​Cross-publisher leaderboard

​Flip view: which publishers carry the most podcasts in a given bias bucket?

​Methodology notes

What the profile gives you

The bias scale

Get a publisher’s bias profile

List a publisher’s analyzed podcasts

Cross-publisher leaderboard

Flip view: which publishers carry the most podcasts in a given bias bucket?

Methodology notes