# Steam Reviews Export with Sentiment (CSV/JSON) (`badboxx_newlife/steam-reviews-export-sentiment`) Actor

- **URL**: https://apify.com/badboxx_newlife/steam-reviews-export-sentiment.md
- **Developed by:** [Francesco Correnti](https://apify.com/badboxx_newlife) (community)
- **Categories:** Other, Social media
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$1.00 / 1,000 review exporteds

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

## Steam Reviews Export with Sentiment (CSV/JSON)

Export **Steam reviews** for one or more games as CSV or JSON, with an offline **sentiment** column per review. Uses the public Steam store reviews endpoint, no API key. For indie devs, marketers and analysts. **$0.001 per review.**

### Input

```json
{ "games": ["570", "https://store.steampowered.com/app/440/Team_Fortress_2/"], "language": "english", "dateFrom": "2026-01-01", "dateTo": "2026-03-31", "maxReviews": 500 }
```

| Field | Default | Meaning |
|---|---|---|
| `games` | required | Appids (`570`) or store URLs. Parsed with `/app/(\d+)` or plain digits; invalid entries are logged and skipped |
| `language` | english | Steam API language code, `all` allowed |
| `dateFrom`, `dateTo` | none | `YYYY-MM-DD`, UTC, both ends inclusive, on review creation time |
| `maxReviews` | 100 | TOTAL across all games (min 1) |

### Output schema

One dataset item per review, these 14 keys: `appId` (int), `reviewId` (str), `url`, `text`, `language`, `date` (ISO 8601 UTC), `votedUp` (bool), `votesUp`, `votesFunny`, `playtimeForeverMin`, `playtimeAtReviewMin` (int minutes), `lexiconScore`, `sentimentScore` (float), `sentiment` (str).

```json
{"appId": 570, "reviewId": "123456", "url": "https://steamcommunity.com/profiles/7656119800000000/recommended/570/", "text": "great fun game", "language": "english", "date": "2026-03-01T12:00:00Z", "votedUp": true, "votesUp": 3, "votesFunny": 0, "playtimeForeverMin": 5400, "playtimeAtReviewMin": 1200, "lexiconScore": 1.0, "sentimentScore": 1.0, "sentiment": "positive"}
```

### Sentiment method

Pure stdlib, no external API. Text is lowercased into word tokens and matched against embedded lists of 40+ positive and 40+ negative gaming words (fun, masterpiece, addictive / boring, buggy, crash, refund, ...). A negator (`not, no, never, don't, isn't, wasn't, can't`) within the 2 previous tokens flips that word.

- `lexiconScore = (pos - neg) / max(1, pos + neg)`, range \[-1, 1], 0 when no hits
- `sentimentScore = round(0.5 * (1 if votedUp else -1) + 0.5 * lexiconScore, 3)`
- `sentiment`: `positive` if score > 0.2, `negative` if < -0.2, else `mixed`

### Pricing

Pay per event: **`review` = $0.001** per review pushed. The run stops cleanly when your max-charge limit is reached.

### Limits

- Public reviews only.
- Steam rate limits apply: 429/5xx retried up to 3 times with backoff, 0.5-1 s pause between pages.
- `filter=recent` walks back in time, so old date windows cost many requests.
- The lexicon is English-only; other languages rely mostly on `votedUp`.
- Max per run = `maxReviews`, total across games.

# Actor input Schema

## `games` (type: `array`):

Steam appids (570) or store URLs (https://store.steampowered.com/app/570/Dota_2/). Invalid entries are logged and skipped.

## `language` (type: `string`):

Steam API language code, e.g. english, german, or all. The sentiment lexicon is English-only.

## `dateFrom` (type: `string`):

UTC, YYYY-MM-DD, inclusive. Optional.

## `dateTo` (type: `string`):

UTC, YYYY-MM-DD, inclusive. Optional.

## `maxReviews` (type: `integer`):

TOTAL reviews across all games. One review is charged each.

## Actor input object example

```json
{
  "language": "english",
  "maxReviews": 100
}
```

# Actor output Schema

## `reviews` (type: `string`):

No description

## `csv` (type: `string`):

No description

# 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("badboxx_newlife/steam-reviews-export-sentiment").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("badboxx_newlife/steam-reviews-export-sentiment").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 '{}' |
apify call badboxx_newlife/steam-reviews-export-sentiment --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,badboxx_newlife/steam-reviews-export-sentiment"
        }
    }
}
```

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/6S8GqHrUBC6DfeRKp/builds/D2FPjdL0gsxGDuMBh/openapi.json