# Collect tweets about a hashtag for research

**Use case:** 

Build a dataset for a study. Give a hashtag and a period of time, and receive one row for each tweet with the text, the language, the author, and the engagement counts. The official API of X starts at $100 each month and offers no academic price. This task needs no key.

## Input

```json
{
  "source_mode": "search",
  "search_query": "from:elonmusk",
  "profile_urls": [],
  "relationship": "followers",
  "search_sort": "Top",
  "since": "2026-08-01",
  "until": "2026-09-01",
  "lang": "en",
  "all_words": [],
  "any_words": [],
  "exact_phrases": [],
  "exclude_words": [],
  "hashtags_any": [
    "climatechange"
  ],
  "hashtags_exclude": [],
  "from_users": [],
  "to_users": [],
  "mentioning_users": [],
  "tweet_type": "all",
  "verified_only": false,
  "blue_verified_only": false,
  "has_images": false,
  "has_videos": false,
  "has_links": false,
  "has_mentions": false,
  "has_hashtags": false,
  "min_likes": 0,
  "min_replies": 0,
  "min_retweets": 0,
  "place": "",
  "geocode": "",
  "near": "",
  "within": "",
  "max_items": 1000
}
```

## Output

```json
{
  "tweet_url": {
    "label": "Tweet URL",
    "format": "string"
  },
  "id": {
    "label": "Tweet ID",
    "format": "string"
  },
  "text": {
    "label": "Text",
    "format": "string"
  },
  "retweet_count": {
    "label": "Retweets",
    "format": "number"
  },
  "reply_count": {
    "label": "Replies",
    "format": "number"
  },
  "favorite_count": {
    "label": "Likes",
    "format": "number"
  },
  "quote_count": {
    "label": "Quotes",
    "format": "number"
  },
  "created_at": {
    "label": "Created At",
    "format": "string"
  },
  "bookmark_count": {
    "label": "Bookmarks",
    "format": "number"
  },
  "lang": {
    "label": "Language",
    "format": "string"
  },
  "handle": {
    "label": "User Handle",
    "format": "string"
  },
  "user.followers_count": {
    "label": "Followers",
    "format": "number"
  },
  "source_root": {
    "label": "Source Root",
    "format": "string"
  },
  "source_value": {
    "label": "Source",
    "format": "string"
  }
}
```

## About this Actor

This example demonstrates how to use [Scweet Twitter/X Scraper](https://apify.com/altimis/scweet.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/altimis/scweet.md) to learn more, explore other use cases, and run it yourself.


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

- **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 full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/altimis/scweet.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).