curl -H "X-API-Key: $PARTICLE_API_KEY" \
"https://api.particle.pro/v1/podcasts/mentions/share-of-voice/compare?by=sentiment&speakers=all"{
"by": "sentiment",
"end": "<string>",
"speakers": "all",
"start": "<string>",
"subjects": [
{
"attributed_mentions": 123,
"by": "occupation",
"end": "<string>",
"groups": [
{
"code": "<string>",
"episodes": 123,
"mentions": 123,
"share": 123,
"speakers": 123,
"title": "<string>",
"breakdown": [
{
"label": "<string>",
"mentions": 123,
"share": 123,
"examples": [
{
"episode": {
"id": "<string>",
"title": "<string>",
"podcast": {
"id": "<string>",
"title": "<string>",
"best_rank": {
"captured_at": "2023-11-07T05:31:56Z",
"chart_type": "top_podcasts",
"rank": 123,
"source": "apple",
"category_slug": "<string>",
"country": "<string>"
},
"image_url": "<string>",
"popularity": 123,
"publisher": {
"id": "<string>",
"name": "<string>",
"slug": "<string>"
},
"slug": "<string>"
},
"published_at": "2023-11-07T05:31:56Z",
"slug": "<string>",
"web_url": "<string>"
},
"line": {
"end_seconds": 123,
"number": 123,
"speaker": "<string>",
"start_seconds": 123,
"text": "<string>",
"is_match": true,
"is_mention": true,
"matched_terms": [
"<string>"
],
"role": "<string>",
"segment_id": "<string>",
"speaker_statement_characteristics": {
"certainty": "hedged",
"sentiment": "negative",
"specificity": "vague",
"temporal_orientation": "past"
}
},
"start_seconds": 123,
"person": {
"id": "<string>",
"name": "<string>",
"description": "<string>",
"image_url": "<string>",
"slug": "<string>"
},
"url": "<string>"
}
]
}
],
"buckets": [
{
"mentions": 123,
"start": "<string>"
}
],
"examples": [
{
"episode": {
"id": "<string>",
"title": "<string>",
"podcast": {
"id": "<string>",
"title": "<string>",
"best_rank": {
"captured_at": "2023-11-07T05:31:56Z",
"chart_type": "top_podcasts",
"rank": 123,
"source": "apple",
"category_slug": "<string>",
"country": "<string>"
},
"image_url": "<string>",
"popularity": 123,
"publisher": {
"id": "<string>",
"name": "<string>",
"slug": "<string>"
},
"slug": "<string>"
},
"published_at": "2023-11-07T05:31:56Z",
"slug": "<string>",
"web_url": "<string>"
},
"line": {
"end_seconds": 123,
"number": 123,
"speaker": "<string>",
"start_seconds": 123,
"text": "<string>",
"is_match": true,
"is_mention": true,
"matched_terms": [
"<string>"
],
"role": "<string>",
"segment_id": "<string>",
"speaker_statement_characteristics": {
"certainty": "hedged",
"sentiment": "negative",
"specificity": "vague",
"temporal_orientation": "past"
}
},
"start_seconds": 123,
"person": {
"id": "<string>",
"name": "<string>",
"description": "<string>",
"image_url": "<string>",
"slug": "<string>"
},
"url": "<string>"
}
],
"low_sample": true,
"scored_mentions": 123,
"top": {
"code": "<string>",
"share": 123,
"title": "<string>"
}
}
],
"host_mentions": 123,
"mentions": 123,
"speaker_mentions": 123,
"speakers": "all",
"start": "<string>",
"breakdown": "sentiment",
"characteristics_version": "<string>",
"company": {
"id": "<string>",
"name": "<string>",
"description": "<string>",
"domain": "<string>",
"image_url": "<string>",
"slug": "<string>",
"ticker": "<string>"
},
"entity": {
"id": "<string>",
"name": "<string>",
"slug": "<string>",
"company": {
"id": "<string>",
"domain": "<string>",
"ticker": "<string>"
},
"description": "<string>",
"image_url": "<string>",
"person": {
"id": "<string>",
"company": "<string>",
"image_url": "<string>",
"title": "<string>"
},
"type": {
"name": "<string>",
"slug": "<string>"
},
"wikipedia_url": "<string>"
},
"keyword": "<string>",
"level": "major",
"scored_mentions": 123
}
],
"breakdown": "sentiment",
"characteristics_version": "<string>"
}{
"detail": "Property foo is required but is missing.",
"error_code": "<string>",
"errors": [
{
"location": "<string>",
"message": "<string>",
"value": "<unknown>"
}
],
"instance": "https://example.com/error-log/abc123",
"resolve": {
"message": "<string>",
"action": "<string>",
"endpoint": "<string>",
"method": "<string>",
"url": "<string>"
},
"status": 400,
"title": "Bad Request",
"type": "https://example.com/errors/example"
}Compare how subjects are spoken of
Sets two to five entities’ or companies’ share of voice by one speaker statement characteristics axis side by side, over the same window, speakers and filter: how NVIDIA is spoken of next to AMD and Intel. Each subject is exactly the split GET /v1/podcasts/mentions/share-of-voice returns for it with by set to the axis: one group per label, each a share of the subject’s scored_mentions and flagged low_sample below 20. Subjects are returned in the order given. A subject that matches nothing, or a company with no linked entity, is a 422 naming it. by defaults to sentiment; breakdown splits each label group by a second axis. For which professions say it, use the share of voice with by=occupation, one subject at a time.
curl -H "X-API-Key: $PARTICLE_API_KEY" \
"https://api.particle.pro/v1/podcasts/mentions/share-of-voice/compare?by=sentiment&speakers=all"{
"by": "sentiment",
"end": "<string>",
"speakers": "all",
"start": "<string>",
"subjects": [
{
"attributed_mentions": 123,
"by": "occupation",
"end": "<string>",
"groups": [
{
"code": "<string>",
"episodes": 123,
"mentions": 123,
"share": 123,
"speakers": 123,
"title": "<string>",
"breakdown": [
{
"label": "<string>",
"mentions": 123,
"share": 123,
"examples": [
{
"episode": {
"id": "<string>",
"title": "<string>",
"podcast": {
"id": "<string>",
"title": "<string>",
"best_rank": {
"captured_at": "2023-11-07T05:31:56Z",
"chart_type": "top_podcasts",
"rank": 123,
"source": "apple",
"category_slug": "<string>",
"country": "<string>"
},
"image_url": "<string>",
"popularity": 123,
"publisher": {
"id": "<string>",
"name": "<string>",
"slug": "<string>"
},
"slug": "<string>"
},
"published_at": "2023-11-07T05:31:56Z",
"slug": "<string>",
"web_url": "<string>"
},
"line": {
"end_seconds": 123,
"number": 123,
"speaker": "<string>",
"start_seconds": 123,
"text": "<string>",
"is_match": true,
"is_mention": true,
"matched_terms": [
"<string>"
],
"role": "<string>",
"segment_id": "<string>",
"speaker_statement_characteristics": {
"certainty": "hedged",
"sentiment": "negative",
"specificity": "vague",
"temporal_orientation": "past"
}
},
"start_seconds": 123,
"person": {
"id": "<string>",
"name": "<string>",
"description": "<string>",
"image_url": "<string>",
"slug": "<string>"
},
"url": "<string>"
}
]
}
],
"buckets": [
{
"mentions": 123,
"start": "<string>"
}
],
"examples": [
{
"episode": {
"id": "<string>",
"title": "<string>",
"podcast": {
"id": "<string>",
"title": "<string>",
"best_rank": {
"captured_at": "2023-11-07T05:31:56Z",
"chart_type": "top_podcasts",
"rank": 123,
"source": "apple",
"category_slug": "<string>",
"country": "<string>"
},
"image_url": "<string>",
"popularity": 123,
"publisher": {
"id": "<string>",
"name": "<string>",
"slug": "<string>"
},
"slug": "<string>"
},
"published_at": "2023-11-07T05:31:56Z",
"slug": "<string>",
"web_url": "<string>"
},
"line": {
"end_seconds": 123,
"number": 123,
"speaker": "<string>",
"start_seconds": 123,
"text": "<string>",
"is_match": true,
"is_mention": true,
"matched_terms": [
"<string>"
],
"role": "<string>",
"segment_id": "<string>",
"speaker_statement_characteristics": {
"certainty": "hedged",
"sentiment": "negative",
"specificity": "vague",
"temporal_orientation": "past"
}
},
"start_seconds": 123,
"person": {
"id": "<string>",
"name": "<string>",
"description": "<string>",
"image_url": "<string>",
"slug": "<string>"
},
"url": "<string>"
}
],
"low_sample": true,
"scored_mentions": 123,
"top": {
"code": "<string>",
"share": 123,
"title": "<string>"
}
}
],
"host_mentions": 123,
"mentions": 123,
"speaker_mentions": 123,
"speakers": "all",
"start": "<string>",
"breakdown": "sentiment",
"characteristics_version": "<string>",
"company": {
"id": "<string>",
"name": "<string>",
"description": "<string>",
"domain": "<string>",
"image_url": "<string>",
"slug": "<string>",
"ticker": "<string>"
},
"entity": {
"id": "<string>",
"name": "<string>",
"slug": "<string>",
"company": {
"id": "<string>",
"domain": "<string>",
"ticker": "<string>"
},
"description": "<string>",
"image_url": "<string>",
"person": {
"id": "<string>",
"company": "<string>",
"image_url": "<string>",
"title": "<string>"
},
"type": {
"name": "<string>",
"slug": "<string>"
},
"wikipedia_url": "<string>"
},
"keyword": "<string>",
"level": "major",
"scored_mentions": 123
}
],
"breakdown": "sentiment",
"characteristics_version": "<string>"
}{
"detail": "Property foo is required but is missing.",
"error_code": "<string>",
"errors": [
{
"location": "<string>",
"message": "<string>",
"value": "<unknown>"
}
],
"instance": "https://example.com/error-log/abc123",
"resolve": {
"message": "<string>",
"action": "<string>",
"endpoint": "<string>",
"method": "<string>",
"url": "<string>"
},
"status": 400,
"title": "Bad Request",
"type": "https://example.com/errors/example"
}Authorizations
Pass your API key in the X-API-Key header (recommended).
Query Parameters
Two to five entity slugs (e.g., 'sam-altman') or IDs, comma-separated, in the order to compare them. One of entity_id or company_id is required.
["sam-altman", "dario-amodei"]
Two to five company slugs, domains, or IDs, comma-separated, in the order to compare them. Each resolves to the company's linked entity. One of entity_id or company_id is required.
["nvidia", "amd", "intel"]
Not accepted: speaker statement characteristics are read on an entity's or a company's mentions, not on the lines that say a keyword, so passing it returns 422.
500The speaker statement characteristics axis whose labels each subject's lines are grouped by: by=sentiment is how negatively or positively each subject was spoken of.
sentiment, certainty, specificity, temporal_orientation Attribute every speaker's lines, hosts included, or guests' and panelists' only.
all, guests Restrict to mentions inside one podcast.
Restrict to mentions on podcasts attributed to one publisher (network), by slug or ID.
Mentions inside ad reads are excluded by default. Pass true to include them.
Only episodes published on or after this date. Defaults to 30 days before until; the window may span at most 365 days.
"2026-09-01"
Only episodes published on or before this date. Defaults to now.
"2026-10-01"
Deprecated alias of since.
Deprecated alias of until.
Also split each label group's lines by their label on this second axis: by=temporal_orientation&breakdown=certainty is how sure each subject's predictions are. Must differ from by.
sentiment, certainty, specificity, temporal_orientation Count only mentions said a certain way, for every subject: speaker_statement_characteristics[temporal_orientation]=future compares how each subject's predictions lean. Each key is an axis (sentiment, certainty, specificity, temporal_orientation) and its value one or more of that axis's labels, comma-separated: labels on one axis match any of them, and axes combine with AND.
Show child attributes
Show child attributes
Response
OK
The speaker statement characteristics axis whose labels every subject's groups are.
sentiment, certainty, specificity, temporal_orientation Day the window ends (UTC), excluded: the window is [start, end).
Whose lines every subject's groups count: every speaker's, or guests' and panelists' only.
all, guests First day of the window (UTC), included.
One split per subject, in the order requested, each exactly what GET /v1/podcasts/mentions/share-of-voice returns for that subject with the same parameters.
Show child attributes
Show child attributes
The axis each label group's lines are split by, when breakdown was given.
sentiment, certainty, specificity, temporal_orientation Opaque version of the speaker statement characteristics every subject read. Absent when no subject read any, or when they read different versions: compare subjects only when it is present.
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