# Text Sentiment Analysis (`easyapi/text-sentiment-analysis`) Actor

Analyze the sentiment of your text, submit single or multiple lines of text and receive a detailed report, including the number of lines analyzed and the breakdown of sentiments (positive, negative, neutral). Gain insights into the emotional tone of your content effortlessly!

- **URL**: https://apify.com/easyapi/text-sentiment-analysis.md
- **Developed by:** [EasyApi](https://apify.com/easyapi) (community)
- **Categories:** AI, Developer tools, Integrations
- **Stats:** 44 total users, 1 monthly users, 100.0% runs succeeded, 3 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.99 / 1,000 results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## 📊 Text Sentiment Analysis API

Analyze the sentiment of your text with our Sentiment Analysis API! Pass single or multiple lines of text and receive a detailed sentiment analysis report that reveals the emotional tone of your content.

### 🌟 Key Features

- **Comprehensive Analysis**: Evaluate text or paragraphs to determine their overall sentiment.
- **Detailed Reporting**: Get insights on the number of lines analyzed and the distribution of sentiments (positive, negative, neutral).
- **Flexible Input**: Accepts both single-line and multi-line text inputs for versatile usage.

### 🚀 How It Works

Simply submit your text to the API, and it will return a comprehensive sentiment analysis report, helping you understand the emotional context of your content.

### 🌍 Start Analyzing Today!

Enhance your applications with valuable sentiment insights. Use our API to gauge public opinion, customer feedback, or any text-based data effortlessly!

#### Input

A full explanation of an input example in JSON.

```
{
  "text": "I am not very happy"
}
```

#### Output sample

The results will be wrapped into a dataset which you can always find in the **Storage** tab. Here's an excerpt from the data you'd get if you apply the input parameters above:

And here is the same data but in JSON. You can choose in which format to download your data: JSON, JSONL, Excel spreadsheet, HTML table, CSV, or XML.

```
[
  {
    "Sentiment": "negative",
    "Value": 0.99598
  }
]
```

# Actor input Schema

## `text` (type: `string`):

The text or paragraphs want to analyze.

## Actor input object example

```json
{
  "text": "I am not very happy"
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("easyapi/text-sentiment-analysis").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("easyapi/text-sentiment-analysis").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call easyapi/text-sentiment-analysis --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=easyapi/text-sentiment-analysis",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/2LdaLZwSZvzV3Iqds/builds/9Ki4vRCakGNDNsgqN/openapi.json