> ## Documentation Index
> Fetch the complete documentation index at: https://docs.particle.pro/llms.txt
> Use this file to discover all available pages before exploring further.

# particle_person_get_statement_characteristics

> How a person speaks on podcasts, and how that moves: their lines' sentiment, certainty, specificity and temporal orientation as shares, per week or month.

How a person speaks on podcasts, and how that moves over time. It reports the share of their lines on each axis:

* **Sentiment:** negative, neutral or positive.
* **Certainty:** hedged, neutral or confident.
* **Specificity:** vague, neutral or specific.
* **Temporal orientation:** about the past, the present or the future.

Each axis is shown for the whole window (the last year by default) and per week or month. Use it for questions like "is Sam Altman more cautious than he used to be?" or "how often does she make predictions?". The labels are the ones [speaker statement characteristics](https://docs.particle.pro/podcasts/speaker-statement-characteristics.md) puts on transcript lines.

Shares are of the person's **scored lines**: lines spoken by them, in any role, that carry characteristics. Lines too short to read carry none. `low_sample` marks a share with fewer than 20 scored lines behind it. Read such a share as an example, not a distribution.

To find their lines said a certain way about a topic, use [`particle_podcast_search_transcripts`](https://docs.particle.pro/mcp/tools/podcasts/podcast-search-transcripts) with `person_slug` and `speaker_statement_characteristics`. Resolve the person first with [`particle_person_resolve`](https://docs.particle.pro/mcp/tools/people/person-resolve).

## Inputs

| Field | Type | Required | Default | Description |
| - | - | - | - | - |
| `person_slug` | string | yes | — | Canonical person slug from `particle_person_resolve` (e.g. `"sam-altman"`), or the encoded person ID. |
| `published_after` | string | no | a year before `published_before` | Start of the window (ISO 8601 date or date-time). |
| `published_before` | string | no | now | End of the window. A bare date includes that whole UTC day. |
| `interval` | enum | no | `month` | `week` (weeks start on Monday, UTC) or `month`. |
| `include` | array of enums | no | `[]` | `examples` adds each bucket's strongest line for every outer label (negative/positive, hedged/confident, vague/specific, past/future), with its episode and a link that plays it. |

## Output

A markdown document headed `## How <name> speaks`:

* `**Window:**`, `**Scored lines:**` (with the number of episodes) and `**Characteristics version:**` rows.
* `### Overall`: one bullet per axis, listing its labels in order with their shares.
* `### By month` (or `### By week`): a table with a row per bucket, zero-filled. Each row gives the scored lines and each axis's label shares. A bucket the window cuts through is marked `(partial)`. A bucket with fewer than 20 scored lines is marked `(low sample)`.
* With `include: ["examples"]`, a `### Strongest lines, <bucket start>` section per bucket. Each bullet reads `**label** (axis): "text" — Episode on Podcast (episode_slug …) <link>`.

The strongest line for a label is the one reading furthest past the label's cut. Neither the readings nor the strength are exposed.

Sample (`person_slug="sam-altman", interval="month", include=["examples"]`, truncated):

```markdown theme={"dark"}
## How Sam Altman speaks

**Window:** 2025-10-01 to 2026-10-27 (exclusive), by month
**Scored lines:** 9619 in 765 episodes
**Characteristics version:** 1

### Overall

- **Sentiment:** negative 10%, neutral 66%, positive 23%
- **Certainty:** hedged 27%, neutral 70%, confident 3%
- **Specificity:** vague 39%, neutral 57%, specific 4%
- **Temporal orientation:** past 17%, present 67%, future 16%

### By month

| Start | Lines | Sentiment | Certainty | Specificity | Temporal orientation |
| --- | --- | --- | --- | --- | --- |
| 2026-10-01 (partial) | 2528 | negative 12%, neutral 64%, positive 23% | hedged 28%, neutral 69%, confident 3% | vague 39%, neutral 57%, specific 4% | past 14%, present 72%, future 14% |

### Strongest lines, 2026-10-01

- **confident** (certainty): "We are clearly going to pick doing the right thing for humanity." — From Fair Game: Sam Altman Talks Elon Musk, ‘Artificial,’ and the Future of Humanity (Part 1 of 2) on Still Watching (episode_slug from-fair-game-sam-altman-talks-elon-musk-artificial-and-the-future-of-humanity) https://radar.particle.pro/podcasts/still-watching/episodes/from-fair-game-sam-altman-talks-elon-musk-artificial-and-the-future-of-humanity?t=1481.9
```

With `output_format=json`, the response is the REST body of `GET /v1/people/{id}/statement-characteristics`. It has:

* `scored_lines`, `episodes`, `low_sample` and `characteristics_version`.
* `characteristics`: one array per axis of `{label, lines, share}`.
* `buckets`: each with the same fields, plus `examples`. Every example carries the line's `speaker_statement_characteristics` and its `episode`.


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