# Bulk Text Sentiment Analyzer (Reviews, Comments, Posts) (`mediapro-tools/bulk-text-sentiment-analyzer`) Actor

Score the sentiment of thousands of texts in seconds. No login. Export JSON/CSV/Excel. Pay only per result.

- **URL**: https://apify.com/mediapro-tools/bulk-text-sentiment-analyzer.md
- **Developed by:** [Jeremy Yarbrough](https://apify.com/mediapro-tools) (community)
- **Categories:** AI, Marketing, Automation
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$0.20 / 1,000 text scoreds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

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 examples already wired to this Actor's own input schema, see the [API](#api) section below.

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`).

# README

## Bulk Text Sentiment Analyzer (Reviews, Comments, Posts)

**Score the sentiment of thousands of texts in seconds, with no login, no browser and no code. Export to JSON, CSV or Excel, or use the API.**

Score the sentiment of thousands of texts in seconds: positive/negative/neutral label plus compound, positive, negative and neutral scores, optional per-sentence breakdown. Paste texts or point it at any Apify dataset (e.g. reviews or social posts from another Actor). Uses the open VADER model locally: no LLM or API costs.

### Use cases

- Score product or app reviews scraped by other Actors
- Track customer-feedback mood over time
- Triage support tickets or comments by negativity

### Input

| Field | Type | Notes |
|---|---|---|
| `texts` | array | One text per line (reviews, comments, posts...). |
| `datasetId` | string | Score items from another run's dataset. |
| `textField` | string | Field holding the text in dataset items. |
| `maxItems` | integer |  |
| `splitSentences` | boolean |  |

### Example input

```json
{
 "texts": [
  "I love this camera, the photos are stunning!",
  "Shipping took forever and the box was damaged. Very disappointed.",
  "The package arrived on Tuesday.",
  "Not bad at all :) would buy again",
  "",
  "Customer service was helpful, but the product broke after a week."
 ],
 "splitSentences": true
}
```

### Output

One dataset item per result. Main columns: `text`, `sentiment`, `compound`, `positive`, `negative`, `neutral`, `words`, `error`. A `RUN_SUMMARY` record is saved to the default key-value store. See the sample output in the Output tab.

### Example output

```json
{
  "text": "I love this camera, the photos are stunning!",
  "sentiment": "positive",
  "compound": 0.7959,
  "positive": 0.587,
  "negative": 0,
  "neutral": 0.413,
  "words": 8,
  "sentences": [
    {
      "sentence": "I love this camera, the photos are stunning!",
      "compound": 0.7959,
      "sentiment": "positive"
    }
  ]
}
```

### Pricing

Pay per result, with no monthly rental or subscription:

- **Text scored**: $0.0002

Example: 1,000 results cost about $0.20 in fees. Apify's free plan includes $5 of monthly credit, which is enough to test this Actor.

### FAQ

**Do I need an account, cookies or a login for the source site?** No. Bulk Text Sentiment Analyzer uses public data sources only, so there is nothing to connect and no account to risk.

**How much will a run cost?** You pay only for results delivered (see Pricing above), plus Apify platform usage, which the free plan's monthly credit easily covers for test runs. Start with a small limit to see the exact cost per run.

**Can I export to CSV, Excel or Google Sheets?** Yes. Every run's dataset can be downloaded as JSON, CSV, Excel, XML or HTML, or pushed to Google Sheets, Make, Zapier, n8n, Slack or a webhook through Apify integrations.

**Can I run it on a schedule or from my own code?** Yes. Add an Apify Schedule (hourly, daily, weekly) or call it through the Apify API / Python & JavaScript clients. It also works with AI agents through the Apify MCP server.

**What happens if an input is invalid or a source is down?** The run keeps going. The bad input gets a row with an `error` field so you can see what failed, and you are not charged for results that were not delivered.

**Is this legal to use?** It collects publicly available data. You are responsible for using the output in line with the source's terms and privacy laws such as GDPR/CCPA; don't use it for spam.

**Something missing or broken?** Open an issue on the Issues tab. Feature requests are usually added within a few days.

### Scheduling / monitoring

Create a Schedule (daily/weekly) and connect a webhook or Slack/email integration.

### Fair use

Official public APIs only, no login. Do not use output for spam or harassment. Respect the data sources' rate limits and terms.

# Actor input Schema

## `texts` (type: `array`):

One text per line (reviews, comments, posts...).

## `datasetId` (type: `string`):

Score items from another run's dataset.

## `textField` (type: `string`):

Field holding the text in dataset items.

## `maxItems` (type: `integer`):

No description

## `splitSentences` (type: `boolean`):

No description

## Actor input object example

```json
{
  "texts": [
    "I love this camera, the photos are stunning!",
    "Shipping took forever and the box was damaged."
  ],
  "datasetId": "",
  "textField": "text",
  "maxItems": 100000,
  "splitSentences": false
}
```

# Actor output Schema

## `results` (type: `string`):

All result records in the default dataset (table view: overview).

## `summary` (type: `string`):

Counts and stats for this run (JSON).

# 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 = {
    "texts": [
        "I love this camera, the photos are stunning!",
        "Shipping took forever and the box was damaged."
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("mediapro-tools/bulk-text-sentiment-analyzer").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 = { "texts": [
        "I love this camera, the photos are stunning!",
        "Shipping took forever and the box was damaged.",
    ] }

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

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

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

```

## CLI example

```bash
echo '{
  "texts": [
    "I love this camera, the photos are stunning!",
    "Shipping took forever and the box was damaged."
  ]
}' |
apify call mediapro-tools/bulk-text-sentiment-analyzer --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,mediapro-tools/bulk-text-sentiment-analyzer"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/vZeC5oKDFUoFbFzvd/builds/DJRdkg7tEOqRqu6g3/openapi.json