# Telegram App Store Reviews - Sentiment and Issues

**Use case:** 

What users actually say about Telegram in App Store reviews: recurring complaints, emerging issues and sentiment over time, across ten countries.

## Input

```json
{
  "appIds": [
    "686449807"
  ],
  "countries": [
    "us",
    "gb",
    "de",
    "fr",
    "nl",
    "ca",
    "au",
    "es",
    "it",
    "br"
  ],
  "pagesPerCountry": 3,
  "minMentions": 3,
  "includeHistory": true,
  "historyDays": 180
}
```

## Output

```json
{
  "type": {
    "label": "Type"
  },
  "name": {
    "label": "App"
  },
  "app_id": {
    "label": "App ID"
  },
  "total_reviews": {
    "label": "Reviews"
  },
  "avg_rating": {
    "label": "Avg ★"
  },
  "top_complaints": {
    "label": "Top complaints"
  },
  "top_praise": {
    "label": "Top praise"
  },
  "emerging_issues": {
    "label": "Emerging issues"
  }
}
```

## About this Actor

This example demonstrates how to use [App Store Review Intelligence: Sentiment & Competitor Gaps](https://apify.com/datasignalslab/app-store-review-intelligence.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/datasignalslab/app-store-review-intelligence.md) to learn more, explore other use cases, and run it yourself.


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For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/datasignalslab/app-store-review-intelligence.md

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).