# Truth Social Trends Scraper (`memo23/truthsocial-trends-scraper`) Actor
Truth Social Trends Scraper — capture what's trending right now: trending posts and trending hashtags with engagement and use-count stats plus usage history, in one combined feed. Schedule it on an interval for a trend time-series. Pure HTTP, no browser, no CAPTCHA solver. JSON or CSV out.
- **URL**: https://apify.com/memo23/truthsocial-trends-scraper.md
- **Developed by:** [Muhamed Didovic](https://apify.com/memo23) (community)
- **Categories:** Social media, AI, Agents
- **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $5.00 / 1,000 results
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/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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md).
If your project is in a different language, use 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
Truth Social Trends Scraper
Scrape what's **trending on Truth Social** right now — trending posts (truths) and/or trending hashtags with engagement stats.
| Input you give it | Rows you get back |
|---|---|
| `trendType: posts` | The truths trending platform-wide |
| `trendType: hashtags` | Trending hashtags with use counts |
| `trendType: both` | Both feeds in one run |
> Pure HTTP. No browser, no CAPTCHA solver. One run captures the current trending feed.
### Why Use This Scraper?
- **Trending posts** — the truths gaining traction across the platform right now.
- **Trending hashtags** — with recent-use and total-use counts plus their history.
- **One combined feed** — pull posts, hashtags, or both in a single run.
- **Clean flat rows** — a `trendType` field distinguishes post rows from hashtag rows.
### Overview
This actor captures Truth Social's live trending surface for real-time monitoring, trend research, and content-strategy signals. Post rows carry the full status; hashtag rows carry use counts and a usage history array.
### Supported Inputs
| Input | Example | Notes |
|---|---|---|
| Trend type | `posts` / `hashtags` / `both` | What to capture |
| Max items | `100` | Cap on trending items |
**Not supported:** personalized "for you" feeds or anything behind login — this is the public trending surface.
### Use Cases
| Who | What they pull |
|---|---|
| Trend researchers | A timestamped snapshot of what's trending |
| Content strategists | Trending hashtags to ride for reach |
| Journalists | The posts driving the platform's conversation |
| Data scientists | Trend time-series by scheduling repeat runs |
### How It Works
1. **Input** — choose posts, hashtags, or both.
2. **Fetch** — the actor pulls the trending-truths and/or trends endpoints over a residential proxy.
3. **Emit** — post and hashtag rows land in one dataset, tagged by `trendType`, bounded by `maxItems`.
### Input Configuration
| Field | Type | Notes |
|---|---|---|
| `trendType` | enum | `posts` (default), `hashtags`, `both` |
| `maxItems` | integer | Cap on trending items returned |
| `proxy` | object | Optional — defaults to residential |
#### Example input
```json
{ "trendType": "both", "maxItems": 100 }
````
### Output Overview
Two row shapes in one dataset, distinguished by `trendType`.
### Output Samples
Trending **post** (`trendType: "post"`):
```jsonc
{
"trendType": "post",
"id": "116944012233117845",
"createdAt": "2026-07-18T17:57:59.287Z",
"username": "OAN",
"content": "CENTCOM confirms two U.S. service members…
",
"url": "https://truthsocial.com/@OAN/posts/116944012233117845",
"repliesCount": 210,
"reblogsCount": 640,
"favouritesCount": 2100,
"mediaAttachments": [],
"scrapedAt": "2026-07-19T10:30:00.000Z"
}
```
Trending **hashtag** (`trendType: "hashtag"`):
```jsonc
{
"trendType": "hashtag",
"name": "MAGA",
"url": "https://truthsocial.com/tags/MAGA",
"recentUses": 1840,
"recentAccounts": 1210,
"totalUses": 13920,
"history": [ { "day": "…", "uses": "1840", "accounts": "1210" } ],
"scrapedAt": "2026-07-19T10:30:00.000Z"
}
```
### Key Output Fields
- **Post rows:** `id`, `createdAt`, `username`, `displayName`, `content`, `url`, `repliesCount`, `reblogsCount`, `favouritesCount`, `mediaAttachments`
- **Hashtag rows:** `name`, `url`, `recentUses`, `recentAccounts`, `totalUses`, `history`
- **Common:** `trendType`, `scrapedAt`
### FAQ
**Posts or hashtags?** Either or both — set `trendType`.
**How do I build a trend time-series?** Schedule the actor on Apify to run on an interval; each run is a timestamped snapshot.
**What's in `history`?** Per-day use and account counts for a trending hashtag.
**Do I need my own account?** No — the actor is fully self-contained.
### Support
Found a bug or need a field added? Open an issue on the actor's Issues tab, or email **muhamed.dido@gmail.com**.
### Explore More Scrapers
Pairs with the **Truth Social Hashtag Scraper** and **Truth Social Comment Scraper**. Browse the full catalog at [muhamed-didovic.github.io](https://muhamed-didovic.github.io/).
### ⚠️ Disclaimer
This Actor accesses publicly available trending data on Truth Social for legitimate research, journalism, and market-intelligence purposes. Use of this Actor must comply with Truth Social's Terms of Service and all applicable laws including data-protection regulations (GDPR, CCPA, etc.). The Actor's authors are not responsible for any misuse. We do not store any scraped data; the Actor returns it directly to your Apify dataset for your authorized use.
### SEO Keywords
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# Actor input Schema
## `trendType` (type: `string`):
Trending posts (truths), trending hashtags, or both.
## `maxItems` (type: `integer`):
Maximum trending items to return.
## `proxy` (type: `object`):
Leave empty — the actor routes through its built-in residential proxy. Only set to use your own.
## Actor input object example
```json
{
"trendType": "posts",
"maxItems": 50
}
```
# 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"maxItems": 50
};
// Run the Actor and wait for it to finish
const run = await client.actor("memo23/truthsocial-trends-scraper").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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = { "maxItems": 50 }
# Run the Actor and wait for it to finish
run = client.actor("memo23/truthsocial-trends-scraper").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 '{
"maxItems": 50
}' |
apify call memo23/truthsocial-trends-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=memo23/truthsocial-trends-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Truth Social Trends Scraper",
"description": "Truth Social Trends Scraper — capture what's trending right now: trending posts and trending hashtags with engagement and use-count stats plus usage history, in one combined feed. Schedule it on an interval for a trend time-series. Pure HTTP, no browser, no CAPTCHA solver. JSON or CSV out.",
"version": "0.0",
"x-build-id": "OXiZP5T0dgOQHYCRN"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/memo23~truthsocial-trends-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-memo23-truthsocial-trends-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/memo23~truthsocial-trends-scraper/runs": {
"post": {
"operationId": "runs-sync-memo23-truthsocial-trends-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/memo23~truthsocial-trends-scraper/run-sync": {
"post": {
"operationId": "run-sync-memo23-truthsocial-trends-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"properties": {
"trendType": {
"title": "What to scrape",
"enum": [
"posts",
"hashtags",
"both"
],
"type": "string",
"description": "Trending posts (truths), trending hashtags, or both.",
"default": "posts"
},
"maxItems": {
"title": "Max items",
"minimum": 1,
"type": "integer",
"description": "Maximum trending items to return.",
"default": 200
},
"proxy": {
"title": "Proxy configuration (optional override)",
"type": "object",
"description": "Leave empty — the actor routes through its built-in residential proxy. Only set to use your own."
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```