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Truth Social Scraper: Engagement Analytics

🔍 Truth Social Scraper pulls public posts, profiles, hashtags & engagement (likes, reposts, replies) from Truth Social. 📊 Collect bios, timestamps, media & links; keyword/user filters; CSV/JSON export. 🚀 Ideal for research, monitoring, marketing & OSINT.

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Result type	Extracted fields	Primary use case
Post content & metadata	`id`, `created_at`, `content`, `url`, `in_reply_to_id`, `media_attachments`	Archiving posts, building a timeline, feeding an LLM
Computed engagement analytics	`totalEngagement`, `engagementBreakdown` (`replies`, `reblogs`, `favourites`), `engagementRatePer1kFollowers`, `engagementTier`	Ranking, alerting, virality tracking
Account snapshot	`account.id`, `account.username`, `account.followers_count` (read directly by the Actor; the rest of the account object passes through unchanged)	Reach and audience context for each post
Nested repost / quote	`reblog`, `quote` — native Truth Social objects, cleaned the same way as the parent post	Thread context, tracing what a profile is amplifying

Computed engagement analytics

This is the capability the other Truth Social scrapers on Apify don't have: raw interaction counts turned into a ready-to-use score, not just three separate numbers you have to combine yourself. For every post, the Actor reads replies_count, reblogs_count, and favourites_count from Truth Social's own API response and computes:

{
  "totalEngagement": 30485,
  "engagementBreakdown": { "replies": 2435, "reblogs": 5407, "favourites": 22643 },
  "engagementRatePer1kFollowers": 3.5701,
  "engagementTier": "viral"
}

totalEngagement is replies_count + reblogs_count + favourites_count, each coerced to a non-negative integer (a missing or non-numeric count becomes 0 — never faked). engagementRatePer1kFollowers is totalEngagement ÷ (account.followers_count ÷ 1000), rounded to 4 decimal places, and is null whenever the account's followers_count is missing or 0. engagementTier buckets totalEngagement against fixed thresholds:

`totalEngagement`	`engagementTier`
10,000 or more	`viral`
1,000 – 9,999	`high`
100 – 999	`medium`
0 – 99	`low`

These four fields are computed only on the top-level post — a nested reblog or quote keeps its own native replies_count/reblogs_count/favourites_count but does not get its own totalEngagement, engagementTier, or engagementRatePer1kFollowers. If you need engagement scoring on a reposted or quoted status too, treat its id as its own post and fetch it directly through fetchSinglePostByIdOrUrl.

Account snapshot embedded in every post

Each post carries Truth Social's own account object for its author. The Actor reads account.followers_count directly to compute engagementRatePer1kFollowers, and the dataset view surfaces the account object alongside the post so you don't need a second lookup to know who posted it or how large their audience is. The rest of the account object — display name, avatar, bio, and so on — passes through exactly as Truth Social's API returns it. When followers_count is missing, zero, or not a usable number, engagementRatePer1kFollowers is written as null instead of a computed value — the Actor never substitutes an estimated or default follower count to force a rate out of incomplete data.

Why not build this yourself?

Truth Social does not publish a public developer API the way X/Twitter or Reddit do. The only interface available is the same internal, Mastodon-compatible endpoint that Truth Social's own web and mobile apps call — and it sits behind Cloudflare bot protection. A DIY scraper has to solve Cloudflare challenge pages, TLS fingerprinting, proxy rotation, and 403/429 backoff, and keep re-solving them every time Truth Social's edge configuration changes.

This Actor already implements that layer: a three-tier connection escalation (direct → Apify auto-proxy → Apify residential proxy), with Chrome-131 TLS fingerprinting applied even on the direct tier so a bare, un-proxied request doesn't look like a generic HTTP library to Cloudflare, a curl-cffi Chrome-131 TLS-impersonation fallback that kicks in on residential when a plain HTTPS client gets a 403, exponential backoff on 5xx/429 responses (honoring a server's Retry-After header, capped at 10 minutes), and residential IP-session rotation on repeated blocks — up to 8 rotations before a request gives up. Timelines are paged 40 posts at a time, with a roughly 4.5-second pause (plus jitter) between pages so pagination itself doesn't trip Cloudflare. Across all of that, a single request can be attempted up to 47 times across tiers before the run reports a real failure. None of that is something you configure — it runs automatically on every request, so you get a truthSocialUsername in and structured, engagement-scored posts out, without maintaining a Cloudflare-evasion stack yourself.

What is the difference between engagement count and engagement rate?

Engagement count and engagement rate answer different questions, and mixing them up leads to the wrong conclusion about which post actually performed best. totalEngagement is an absolute count — replies plus reblogs plus favourites — so it naturally favors whichever account has the largest audience; a post from an account with 8 million followers will usually out-count one from an account with 80,000 followers even if the smaller account's post resonated far more with the people who actually saw it.

engagementRatePer1kFollowers normalizes for that: it's totalEngagement divided by the account's followers_count in thousands, so a post is scored against its own audience size, not against every other account in your dataset. That distinction matters most once you're comparing posts across multiple profiles of different sizes — ranking by totalEngagement alone will almost always surface the biggest account's posts, while ranking by engagementRatePer1kFollowers surfaces which posts actually moved their own audience.

Truth Social Scraper: Engagement Analytics returns both on every post — totalEngagement for absolute scale, engagementRatePer1kFollowers for relative resonance — plus engagementTier, which buckets the absolute count into low/medium/high/viral for quick filtering. Use sortByEngagement (which ranks by the absolute totalEngagement) when you want a single profile's biggest posts; read engagementRatePer1kFollowers yourself when comparing across profiles of different sizes.

Open Truth Social Scraper: Engagement Analytics in the Apify Console (or find it on the Apify Store) and click Run.
Enter one or more handles in truthSocialUsername — or expand Advanced and paste post IDs/URLs into fetchSinglePostByIdOrUrl instead.
Set your query controls: maxPosts, onlyFetchReplies, onlyFetchPostsWithMedia, minEngagement, sortByEngagement.
Click Start.
Once the run finishes, download the dataset as JSON, CSV, or Excel from the Storage tab, or pull it with the Apify API.

A real request body, using the Actor's actual parameter names:

{
  "truthSocialUsername": ["realDonaldTrump"],
  "maxPosts": 100,
  "onlyFetchPostsWithMedia": false,
  "minEngagement": 500,
  "sortByEngagement": true
}

How to run multiple queries in one job

truthSocialUsername accepts a list, one handle per line. Add as many profiles as you want scraped in a single run — each one is fetched in turn, up to maxPosts posts per profile, and each keeps its own incremental bookmark when continueFromLastPostId is on, so monitoring ten accounts doesn't mean ten separate Actor runs or ten separate bookmarks to track by hand. There's no documented concurrency setting to raise; multiple usernames in one run are processed sequentially, not in parallel, and minEngagement/sortByEngagement are applied per profile, so each profile's posts are ranked against its own timeline, not pooled together with every other profile in the run.

⬇️ Input

Every field below comes directly from the Actor's input schema. Nothing is required — the schema's required list is empty — but the run needs either a populated truthSocialUsername or a non-empty fetchSinglePostByIdOrUrl; truthSocialUsername ships prefilled with realDonaldTrump so a default run always has a target unless you clear it.

Parameter	Required	Type	Default / range	Description
`truthSocialUsername`	No	array of strings	prefill `["realDonaldTrump"]`	Profile handles to scrape, one per line. The `@` is optional. Ignored when `fetchSinglePostByIdOrUrl` has entries.
`maxPosts`	No	integer	default `20`; min `5`; max `5000`	Number of posts to collect from a profile's timeline. Not used in single-post mode.
`continueFromLastPostId`	No	boolean	default `false`	Only fetch posts newer than the last post ID saved for that username. Cannot be combined with `startFromPostId`.
`onlyFetchReplies`	No	boolean	default `false`	`false` = normal posts only, replies excluded. `true` = replies only.
`onlyFetchPostsWithMedia`	No	boolean	default `false`	Keep only posts with at least one item in `media_attachments`.
`cleanContent`	No	boolean	default `true`	Strip HTML from `content` (and from any nested `reblog`/`quote` content) into plain text.
`minEngagement`	No	integer	default `0`; min `0`	Drop any post whose `totalEngagement` is below this value, before it's pushed to the dataset.
`sortByEngagement`	No	boolean	default `false`	Buffer each profile's kept posts and push them ranked by `totalEngagement`, highest first — still capped at `maxPosts`.
`startFromPostId`	No	string	—	An 18-digit post ID; fetch posts older than this ID. Cannot be combined with `continueFromLastPostId`.
`fetchSinglePostByIdOrUrl`	No	array of strings	—	One or more post IDs or full `truthsocial.com` links. When non-empty, profile-timeline mode is skipped entirely.
`proxyConfiguration`	No	object (Apify Proxy editor)	prefill `{ "useApifyProxy": true }`	Standard Apify Proxy configuration. Optional for most runs — the Actor escalates to residential automatically when needed.

Example full input:

{
  "truthSocialUsername": ["realDonaldTrump", "andypesalva"],
  "maxPosts": 200,
  "continueFromLastPostId": false,
  "onlyFetchReplies": false,
  "onlyFetchPostsWithMedia": false,
  "cleanContent": true,
  "minEngagement": 100,
  "sortByEngagement": true,
  "startFromPostId": "",
  "fetchSinglePostByIdOrUrl": [],
  "proxyConfiguration": { "useApifyProxy": true }
}

Common pitfall: setting continueFromLastPostId and startFromPostId together fails the run before it starts — "Don't combine 'Pick up where you left off' with 'Start older than this post'." Pick one. startFromPostId also has to be exactly 18 digits; anything shorter, longer, or non-numeric is rejected.

Each line in truthSocialUsername is classified independently, not just treated as a bare handle: a plain handle or a full truthsocial.com profile URL is fetched as a timeline, but an entry that parses as a post ID (17–20 digits) or a full post link is fetched as a single post instead — so you can mix profile handles and specific post links or IDs in the same list and get the right thing back for each line without moving anything into fetchSinglePostByIdOrUrl.

When cleanContent is on, the Actor doesn't just strip tags — <br> and <p> become spaces, closing </p>, </div>, and </blockquote> tags add a space, HTML entities are unescaped, and repeated whitespace is collapsed to single spaces, so content reads as plain, trimmed text instead of raw markup. The same cleanup is applied recursively to a nested reblog or quote object's content, not just the top-level post.

If you're calling this Actor programmatically and already have input built for the base field names, the Actor also accepts legacy aliases: username for truthSocialUsername, useLastPostId for continueFromLastPostId, startFromId for startFromPostId, onlyReplies for onlyFetchReplies, onlyMedia for onlyFetchPostsWithMedia, and singlePostId (or urls) for fetchSinglePostByIdOrUrl. The current schema names take precedence when both are present.

⬆️ Output

Each pushed row is the complete post object exactly as Truth Social's API returns it, plus the four computed engagement fields. Nothing the Actor reads is stripped — id, created_at, content, url, in_reply_to_id, media_attachments, the full account object, and (when present) the nested reblog/quote objects all pass through, alongside totalEngagement, engagementBreakdown, engagementRatePer1kFollowers, and engagementTier. Truth Social's response can include additional native fields beyond the ones this Actor reads or filters on — those pass through unmodified too. Results are available from the Storage tab in any format the Apify dataset export supports, including JSON, CSV, and Excel.

The dataset's default table view — named Posts, inside the Collected Truth Social posts dataset — only surfaces 10 columns for readability: id, created_at, content, totalEngagement, engagementTier, engagementRatePer1kFollowers, url, account, media_attachments, and engagementBreakdown. That view is a display subset, not the full row — switch to the JSON view in Storage, or export the dataset, to see everything else the row carries, including replies_count, reblogs_count, favourites_count, in_reply_to_id, and the nested reblog/quote objects.

You're only charged for rows that actually reach the dataset. Each pushed row fires one row_result pay-per-event charge (see the Actor's Pricing tab for the current rate) — a post dropped by minEngagement, excluded by onlyFetchReplies/onlyFetchPostsWithMedia, or a 404 in single-post mode is never pushed, so it's never charged.

Scraped results

[
  {
    "id": "113847449027767807",
    "created_at": "2026-05-18T04:23:30.018Z",
    "content": "Coming up, THE MOST IMPORTANT WEEKEND, PLUS, IN AMERICAN HISTORY. ENJOY! DJT",
    "url": "https://truthsocial.com/@realDonaldTrump/113847449027767807",
    "in_reply_to_id": null,
    "media_attachments": [],
    "account": {
      "id": "107780257626128497",
      "username": "realDonaldTrump",
      "display_name": "Donald J. Trump",
      "followers_count": 8541456,
      "following_count": 71,
      "statuses_count": 24750
    },
    "reblog": null,
    "quote": null,
    "replies_count": 2435,
    "reblogs_count": 5407,
    "favourites_count": 22643,
    "totalEngagement": 30485,
    "engagementBreakdown": { "replies": 2435, "reblogs": 5407, "favourites": 22643 },
    "engagementRatePer1kFollowers": 3.5701,
    "engagementTier": "viral"
  },
  {
    "id": "113852201118845201",
    "created_at": "2026-05-19T11:02:07.441Z",
    "content": "Thank you to everyone who came out today. Historic turnout!",
    "url": "https://truthsocial.com/@realDonaldTrump/113852201118845201",
    "in_reply_to_id": null,
    "media_attachments": [
      { "id": "9910233", "type": "image", "url": "https://static-assets-1.truthsocial.com/example.jpg" }
    ],
    "account": {
      "id": "107780257626128497",
      "username": "realDonaldTrump",
      "display_name": "Donald J. Trump",
      "followers_count": 8541456,
      "following_count": 71,
      "statuses_count": 24751
    },
    "reblog": null,
    "quote": null,
    "replies_count": 512,
    "reblogs_count": 940,
    "favourites_count": 6104,
    "totalEngagement": 7556,
    "engagementBreakdown": { "replies": 512, "reblogs": 940, "favourites": 6104 },
    "engagementRatePer1kFollowers": 0.8846,
    "engagementTier": "high"
  },
  {
    "id": "113860112207730933",
    "created_at": "2026-05-21T09:14:52.109Z",
    "content": "Great meeting today.",
    "url": "https://truthsocial.com/@realDonaldTrump/113860112207730933",
    "in_reply_to_id": null,
    "media_attachments": [],
    "account": {
      "id": "107780257626128497",
      "username": "realDonaldTrump",
      "display_name": "Donald J. Trump",
      "followers_count": 8541456,
      "following_count": 71,
      "statuses_count": 24752
    },
    "reblog": null,
    "quote": null,
    "replies_count": 41,
    "reblogs_count": 23,
    "favourites_count": 210,
    "totalEngagement": 274,
    "engagementBreakdown": { "replies": 41, "reblogs": 23, "favourites": 210 },
    "engagementRatePer1kFollowers": 0.0321,
    "engagementTier": "medium"
  }
]

Political and media monitoring teams: run a watchlist of handles with sortByEngagement on to see which posts from a profile are landing hardest right now, using engagementTier to prioritize what gets a human look first instead of scrolling a raw timeline in arrival order.
AI engineers and LLM developers: an agent issues a run with truthSocialUsername or fetchSinglePostByIdOrUrl, receives back structured JSON with content, totalEngagement, and engagementTier already attached, and passes it to the model as grounded context — no separate scoring step, sentiment model, or post-processing pipeline required before the data is usable.
Market and social researchers: track engagementRatePer1kFollowers across accounts of very different audience sizes to compare relative resonance, not just raw counts that favor whoever has the most followers — useful for cross-account studies where absolute engagement numbers alone would just reflect follower count.
Communications and PR teams: set minEngagement to filter out noise and keep only posts that crossed a threshold worth reporting on, then export straight to CSV for a weekly summary without manually sorting a spreadsheet by a raw like-count column afterward.

📈 How do you monitor engagement over time?

Engagement is not static — a post's totalEngagement and engagementTier at the moment you scrape it is a snapshot, and re-running the same query later gives you a new one. Monitoring means running the same truthSocialUsername set on a schedule and diffing what changed between runs.

The fields to diff between two runs of the same post id: totalEngagement (has it grown, and by how much), engagementBreakdown (is growth coming from replies, reblogs, or favourites), engagementRatePer1kFollowers (is it resonating relative to the account's audience, not just in absolute terms), and engagementTier (has it crossed a bucket boundary — medium to high, or high to viral). A post crossing into viral between two runs is a stronger signal than any single-run number.

A concrete workflow: schedule a run across your watchlist every few hours with sortByEngagement on, keep each run's dataset, and compare the totalEngagement for matching ids against the previous run — alert when a post's engagementTier changes or when totalEngagement jumps past a threshold you care about. For new-post monitoring specifically, turn on continueFromLastPostId so each scheduled run only returns posts you haven't seen yet for that username; this bookmark is stored in the run's key-value store, so it persists across runs when the Actor is triggered repeatedly from the same Apify Task rather than as one-off ad-hoc runs. Point the schedule at an Apify Schedule attached to that Task for the delivery mechanism.

Truth Social Scraper: Engagement Analytics works with any language or tool that can send an HTTP request through the Apify API, or with the official Apify client libraries.

REST API with Python

Install the official client (pip install apify-client), authenticate with an Apify API token, call the Actor by its <username>/<actor-name> slug, wait for the run to finish, and iterate the resulting dataset — the same pattern works for any Apify Actor, not just this one:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")

run = client.actor("<YOUR_USERNAME>/truth-social-engagement-analyzer").call(
    run_input={
        "truthSocialUsername": ["realDonaldTrump"],
        "maxPosts": 100,
        "minEngagement": 500,
        "sortByEngagement": True,
    }
)

for post in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(post["id"], post["totalEngagement"], post["engagementTier"])

Swap <YOUR_APIFY_TOKEN> for a token from your Apify account's Integrations settings, and <YOUR_USERNAME> for the username the Actor is published under — the slug format is the same one shown in this Actor's Apify Console URL and API tab. The same call works from the JavaScript/Node.js apify-client package, or from any HTTP client hitting the Apify REST API directly, since the underlying endpoint is language-agnostic.

MCP for query-grounded AI agents

Any Actor published on the Apify Store — including this one — is callable as a tool through Apify's hosted Model Context Protocol server, without a dedicated MCP build step for this Actor specifically:

{
  "mcpServers": {
    "apify": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://mcp.apify.com/?tools=<YOUR_USERNAME>/truth-social-engagement-analyzer",
        "--header",
        "Authorization: Bearer <YOUR_APIFY_TOKEN>"
      ]
    }
  }
}

An agent in Claude Desktop, Cursor, or another MCP-compatible client can then issue a query, receive the scored posts as structured JSON, and generate an answer grounded in current Truth Social activity instead of training-data knowledge. Because the engagement fields are already computed server-side, the agent doesn't need a second tool call or a scoring prompt to work out which posts mattered most — engagementTier and totalEngagement are already sitting on the object it gets back.

Scheduled monitoring and delivery

The Actor itself has no built-in webhook or polling logic — that's handled at the Apify platform level. Attach an Apify Schedule to a saved Task to run this Actor automatically on an interval, and use Apify webhooks to fire your own endpoint the moment a run finishes, so new rows can flow into a database, alerting tool, or dashboard without you polling for them. Running from a saved Task (rather than one-off runs from the Actor's own page) also matters for continueFromLastPostId: the bookmark the Actor writes to its key-value store is tied to that run's storage, so repeated Task runs are what makes the incremental mode behave as "only new posts since last time" across a schedule.

Scraping public Truth Social posts is generally lawful in the United States — courts have held that accessing data a website makes available to any visitor without a login does not violate the Computer Fraud and Abuse Act (hiQ Labs, Inc. v. LinkedIn Corp., 9th Cir., 2019). Truth Social Scraper: Engagement Analytics returns only what a public profile shows any logged-out visitor; it does not access private accounts, comments requiring authentication, or anything behind a login wall.

Because posts carry account-level personal data (usernames, display names, follower counts), GDPR and CCPA principles around processing personal data can still apply depending on who you are and what you do with it — collection alone is not automatically exempt just because the source is public. Separately, Truth Social's own Terms of Service govern automated access to the platform regardless of data-protection law. Scraping for AI training and scraping for day-to-day monitoring carry different risk profiles — consult your legal team before any commercial use case involving bulk data storage.

❓ Frequently asked questions

totalEngagement is the sum of replies_count, reblogs_count, and favourites_count from Truth Social's own API response for that post, each floored at zero if missing or non-numeric. engagementTier buckets that sum: viral at 10,000+, high from 1,000–9,999, medium from 100–999, low below 100. Both fields are computed on every post the Actor pushes — there's no toggle to turn the calculation off.

How many posts does it return per profile?

Up to maxPosts, which defaults to 20 and can be set between 5 and 5,000 per profile per run. In single-post mode (fetchSinglePostByIdOrUrl), maxPosts is ignored — you get exactly the posts you listed, minus any that return a 404.

Can I filter posts by engagement score or media before they're saved?

Yes. Set minEngagement to drop any post whose totalEngagement falls below that value — filtered posts are never pushed to the dataset, so they're never charged. Turn on onlyFetchPostsWithMedia to keep only posts with at least one image or video attachment, independently of the engagement filter.

It escalates through three connection tiers — direct, Apify's automatic proxy, and Apify residential proxy — switching up a tier on a block or proxy error, and rotating to a fresh residential session on repeated 403s. On residential, a curl-cffi request with Chrome-131 TLS impersonation is tried before falling back to a plain HTTPS client. HTTP 429 responses honor the server's Retry-After header when present, backing off up to 10 minutes between attempts; other retryable errors use exponential backoff. No input parameter controls this — it runs automatically.

How do I fetch a single post instead of a whole profile timeline?

Add the post's ID (a 17–20 digit number) or its full truthsocial.com link to fetchSinglePostByIdOrUrl. As soon as that list has an entry, profile-timeline mode is skipped entirely, even if truthSocialUsername is also filled in — only the listed posts are fetched and scored.

How do I monitor a profile's engagement over time without duplicate posts?

Turn on continueFromLastPostId. Each run for a given username only fetches posts newer than the last one it saved for that username, using a bookmark stored in the run's key-value store. Pair it with an Apify Schedule on a saved Task so the same store — and bookmark — is reused across runs.

Yes. It's callable as an HTTP endpoint through the Apify API by any agent framework, and it's reachable through Apify's hosted MCP server using the command shown above — which lets an MCP-compatible agent (Claude Desktop, Cursor, and others) call it as a tool and get back live, engagement-scored posts mid-conversation.

As observed on their public Apify Store listings on 2026-07-26: bovi/truth-social-scraper returns raw upvote/downvote and link-card fields but no engagement scoring, tiering, or per-follower rate. muhammetakkurtt/truth-social-scraper returns the full raw Mastodon-style status object (visibility, language, tags, poll, and more) plus per-username incremental tracking, but likewise does no engagement computation, filtering, or ranking — that has to happen after export — and its own docs state that a post ID which can't be found still incurs a charge. Neither exposes a built-in minEngagement filter or a sortByEngagement ranking option. Truth Social Scraper: Engagement Analytics adds the computed totalEngagement, engagementBreakdown, engagementRatePer1kFollowers, and engagementTier on every post, plus both of those controls, and does not charge for a post that returns a 404.

What happens if a profile doesn't exist or a post has been deleted?

For profile mode, the Actor looks up the account by handle first; if that lookup fails, the run stops with an error rather than silently returning an empty dataset. For single-post mode or a post URL in the profile list, a post that returns a 404 (deleted, or an invalid ID) is skipped and logged — the run continues with the remaining targets, and you are not charged for the skipped post. Only public accounts are readable at all; there's no separate handling for private or deactivated profiles beyond the errors Truth Social's own API returns for them.

Yes. No Truth Social login, password, or API key is required — the Actor only reads public data. Leaving proxyConfiguration at its default (useApifyProxy: true) is enough; the Actor's own connection escalation handles routing through Apify's proxy tiers as needed, so you don't have to pick a proxy group or manage sessions yourself.

💬 Your feedback

Found a bug or a field that doesn't match what Truth Social actually returns? Let us know through this Actor's Issues tab in Apify Console, or reach Scrapier through your Apify account's contact options — reports like this are what keep the Actor matched to Truth Social's API as it changes.

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