# Score the sentiment of three sample texts

**Use case:** 

Scores three sample texts and returns positive, negative and neutral probabilities for each. The models run inside the actor; no outside service is called. Replace the texts with your own, or point the actor at a dataset in your account.

## Input

```json
{
  "texts": [
    "I love this phone, the battery lasts all day.",
    "The delivery was late and the box was damaged.",
    "The store opens at nine."
  ],
  "textField": "text",
  "maxDatasetItems": 1000,
  "model": "english",
  "level": "document",
  "aspects": [
    "price",
    "delivery",
    "battery"
  ]
}
```

## Output

```json
{
  "index": {
    "label": "#",
    "format": "number"
  },
  "ok": {
    "label": "Scored",
    "format": "boolean"
  },
  "label": {
    "label": "Sentiment",
    "format": "text"
  },
  "compound": {
    "label": "Compound",
    "format": "number"
  },
  "scores": {
    "label": "Scores",
    "format": "object"
  },
  "text": {
    "label": "Text",
    "format": "text"
  },
  "error": {
    "label": "Error",
    "format": "text"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The Sentiment Analyzer: positive, negative and neutral scores Actor is ready to run with the inputs already set for "Score the sentiment of three sample texts". [Sign up or log in](https://console.apify.com/create-task-from-example/SRCVOixSqjCYzk2Nr) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Score the sentiment of three sample texts" task

The Sentiment Analyzer: positive, negative and neutral scores Actor will start running based on the input automatically. You can also change all the input fields, like texts, text field in the dataset items, and more, to match your specific use case.

### 3. Receive the "Score the sentiment of three sample texts" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as #, scored, sentiment, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Score the sentiment of three sample texts" task via API](https://apify.com/examsens.ai/sentiment-analyzer.md).

## About this Actor

This example demonstrates how to use [Sentiment Analyzer: positive, negative and neutral scores](https://apify.com/examsens.ai/sentiment-analyzer.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/examsens.ai/sentiment-analyzer.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/examsens.ai/sentiment-analyzer.md

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).