X Tweet Classifier with AI Analysis | $0.0003/Tweet

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Xquik is the world's fastest & cheapest X (Twitter) scraper service with the most complete X data. Xquik's X (Twitter) Tweet Classifier answers your own questions on every tweet. Ask for labels, scores or yes/no answers. Most other Apify Actors charge before filtering or deduplicating. Xquik charges only for delivered, unique, filter-matching results. AI costs are included in the per-tweet price. You need no AI account, tokens or key.

Classify X (Twitter) posts with your own questions & keep the original tweet data. Xquik's X Tweet Classifier with AI Analysis collects matching tweets. It answers 1 to 8 typed questions per post. Use categories for support triage, scores for prioritization & probabilities for relevance. Presets cover brand monitoring, complaints, competitors, purchase intent, product feedback, news, sentiment & market sentiment. Custom questions replace them.

• Typed answers. Answers carry probabilities, confidence & question versions.
• Your questions, your categories. Each question takes up to 255 categories.
• Complete source records. Every row keeps every field the tweet exposes.
• Filter-first billing. You pay only for unique, filter-matching tweets with a successful analysis.

Xquik is an independent third-party service. Not affiliated with X Corp. "Twitter" and "X" are trademarks of X Corp.

How to classify tweets with custom questions

New to Apify? Create a free account first. The free plan needs no credit card & gives $5 to spend each month. At $0.0003 per analyzed tweet, $5 pays for up to 16,000 analyzed tweets before platform usage. Then come back here & press Try for free.

1. Add tweet URLs, search terms, profile handles or tweet IDs.
2. Set maxItems & the extraction filters your task needs.
3. Add your questions under analysis.questions, or pick a preset with analysis.preset. Without either, the run uses the sentiment preset.
4. Start the run & open the dataset.

Supported modes collect tweets, searches, profile posts, Lists, replies, quotes & threads. Standalone article extraction & user lists are not classification inputs.

{
  "searchTerms": ["\"need a recommendation\" headphones lang:en"],
  "maxItems": 20,
  "analysis": {
    "questions": [
      {
        "id": "buying",
        "type": "probability",
        "version": "1",
        "instructions": "Does the author want to buy headphones?"
      }
    ],
    "targets": [{ "name": "headphones", "aliases": ["headset"] }],
    "context": "Exclude advertisements aimed at other buyers."
  }
}

Questions & limits

Provide 1 to 8 questions with unique IDs, instructions & versions.

• choice uses 2 to 255 named categories with descriptions or null values.
• score uses an ordered levels array with at least 2 descriptions.
• probability returns a value between 0 & 1. Optional criteria contain yes & no descriptions.

The presets are brand, complaints, competitors, purchase_intent, product_feedback, news, sentiment & market. maxContextBytes defaults to 64,000 bytes. A smaller limit cuts long posts to fit & marks them truncated. concurrency defaults to 16 & accepts 1 to 16. Each question definition may use up to 8,000 bytes.

Analyze your own text

Paste your own drafts, replies, reviews or notes in texts. Xquik's X Tweet Classifier analyzes them. It fetches nothing from X.

{
  "texts": [
    "The new update is great, but sync still drops on mobile.",
    "Support fixed my issue in 10 minutes. Thank you."
  ]
}

• Each text becomes 1 row with the same analysis answers as a tweet.
• tweet.id is text:1, text:2 & so on, & tweet.type is text.
• Each analyzed text costs the same $0.0003 as an analyzed tweet.
• With texts set, the run analyzes only those texts. Run X targets separately.

How much does it cost to classify tweets?

Xquik's X Tweet Classifier costs from $0.0003 per analyzed tweet. It charges no start fee. The price includes collection & AI costs. You need no AI account, tokens or key. The price covers up to 8 questions & 64,000 bytes of context per tweet. Each question definition may use up to 8,000 bytes.

For more volume, pick an Apify plan with more prepaid usage.

Extraction filters & deduplication run before analysis. You never pay for filtered-out or duplicate rows. Failed analyses, skipped analyses & diagnostic rows have no result charge. Apify bills platform usage for compute, storage & transfer separately at your plan's rates. The Pricing tab shows it.

Input & output examples

The input above is copy-ready. An abbreviated output row looks like this.

{
  "tweet": { "id": "2100344867507327087", "text": "…", "likeCount": 6409 },
  "analysis": {
    "status": "succeeded",
    "answers": [
      {
        "questionId": "topic",
        "type": "choice",
        "value": "ai_safety",
        "confidence": 0.93
      },
      {
        "questionId": "disclosure",
        "type": "probability",
        "probability": 0.97
      },
      {
        "questionId": "specificity",
        "type": "score",
        "value": 2,
        "confidence": 0.88
      }
    ]
  }
}

Each result contains tweet & analysis. Answers include types, question versions & available probabilities. A row with a failed or skipped analysis keeps the collected tweet & a reason. Its answer list is empty.

Free diagnostics in the key-value store explain invalid inputs, missing results & interrupted collection. The run report separates collected rows, charged analyses & pending charges.

Run summary & flat answers

A run writes an analysis-summary record to its key-value store in 3 cases.

• It hits a problem or is large.
• Its comparison finds a changed, new or not comparable tweet.
• It has alwaysSaveRunRecords on.

Other runs skip the record, including the first run of a series. Their status names the top answer, like Top sentiment is positive in 3 of 5 results. A comparison without a change states No change since the earlier run. A run that hits a problem or is large also writes run-report. So does a run with alwaysSaveRunRecords on. run-report repeats the summary under results.analysisSummary.

The summary counts analyzed, failed & skipped rows. It sums engagement & summarizes every question. Every custom question gets its own block.

• A choice question reports category counts & shares.
• A score question reports its mean & level counts.
• A yes/no question reports yes & no counts.
• Every row lists sourceDomains, the hostnames it links to.
• Every row lists cashtags found in its text, such as $NVDA.
• With monitor.baselineDatasetId set, the summary's monitor block counts comparison statuses. It lists up to 50 changed rows.

The summary rounds numbers to 4 decimals. An empty run reports counts of 0 & null means.

Set analysis.preset to run a built-in preset instead of custom questions. It accepts brand, complaints, purchase_intent, product_feedback, competitors, sentiment, market or news. The summary then reports each question of that preset.

Every result row also carries answers, a flat map keyed by question ID. Each value is the chosen category, score or probability. The Flat answers dataset view & CSV or Excel exports show 1 column per question. The columns sit beside the tweet, so spreadsheets need no JSON parsing. Failed & skipped rows carry an empty map.

Compare with an earlier run

Pass monitor.baselineDatasetId, the dataset ID of a completed earlier run with the same analysis settings. The comparison reads that run's rows. It works even when that run skipped its summary. Every row then gains a monitor object. Its status takes these values.

• first_run without a baseline.
• new_to_baseline for tweets the earlier run did not have.
• unchanged or changed for tweets it had.

changes lists each decision for any of your questions that moved from previous to current. Decisions compare by category, rounded score level or yes/no at 0.5. A decision counts as changed only when it moves clearly. Near ties between runs stay unchanged.

A baseline above maxBaselineRows, or from different settings, stops the run before collection. The run then writes a diagnostic row. maxBaselineRows defaults to 100,000.

Task examples

Choose from 50 public tasks. Each starts from a real English search & a bounded maxItems. It includes ready-made custom questions & the overview dataset view. Edit the search or the questions before running.

• Triage customer support requests on X
• Score sales leads from X posts
• Detect service outage reports on X
• Classify hiring signals on X
• Tag product feature requests on X
• Classify app feedback like store reviews
• Detect scam and fraud warnings on X
• Classify event attendance intent
• Extract restaurant review signals
• Separate crypto promotion from analysis
• Classify persuasive political posts
• Detect subscription churn risk signals

The remaining tasks cover more workflows on the Actor page.

Related Xquik Actors

Every Xquik Actor shares the same extraction engine, filter-first billing & diagnostics. Pick the one that matches the data you need.

• X Tweet Scraper scrapes tweets from searches, profile timelines, Lists & tweet IDs with 50+ filters & flat exports. Use it when you need tweet data without analysis. From $0.00015 per row.
• X Profile Scraper scrapes profiles plus their posts, replies, media & followers from handles, IDs or URLs. Use it when you start from accounts rather than searches. From $0.00015 per row.
• X Reply Scraper scrapes replies, comments & whole conversations under posts with 25+ filters. Use it when you need the discussion beneath tweets. From $0.00015 per row.
• X Engagement Scraper scrapes replies, quotes, retweeters & threads for post URLs or IDs in bulk. Use it when you measure who engaged with posts. From $0.00015 per row.
• X Quote Tweets Scraper scrapes the quote tweets of posts with text, media, counts, authors & 11 filters. Use it when you study who quoted posts & what they said. From $0.00015 per tweet.
• X Follower Scraper scrapes followers, following, List members, subscribers & Community members as profile rows. Use it when you need audience or member lists. From $0.00015 per profile.
• X User Search Scraper searches users by handle, bio & location with follower, verification, age & location filters. Use it when you build account lists from search. From $0.00015 per profile.
• X Account Location Scraper checks where accounts are based with X's "Account based in" label, "connected via" & username changes. Use it when you vet where accounts are based. From $0.00015 per account.
• X Email Scraper gets the emails, phones & links accounts publish on their profiles, from handles, followers or user searches. Use it when you need the emails profiles publish. From $0.00015 per profile.
• X List Scraper scrapes List posts, members & followers from List URLs or IDs. Use it when a curated List defines your sources. From $0.00015 per row.
• X Community Scraper scrapes Community info, posts, searches, members & moderators. Use it when your sources are X Communities. From $0.00015 per row.
• X Space Scraper finds Spaces by keyword & reads their titles, states, times, listener counts, hosts & speakers. It also reads broadcasts by URL or ID. Use it when you track live audio & video on X. From $0.00015 per Space or broadcast.
• X Trends Scraper scrapes real-time trends by location with rank, volume, query & WOEID. Use it when you track what is trending where. From $0.00015 per trend.
• X Jobs Scraper scrapes X job listings by keyword, place, workplace, seniority & company, with salaries & apply links. Use it when you collect job openings posted on X. From $0.00015 per job.
• X Article Scraper scrapes long-form X Articles as Markdown & text with covers, authors, dates & metrics. Use it when you need article bodies, not tweets. From $0.00015 per article.
• X Media Downloader extracts or stores photos, videos & GIFs from posts or profiles with MP4 & metadata options. Use it when you need the media files themselves. From $0.00015 per media row.
• X (Twitter) Brand Monitoring with AI Analysis tracks brand mentions with AI relevance, sentiment & customer-experience answers & compares runs. Use it when you watch a brand over time. From $0.0003 per analyzed tweet.
• X Tweet Sentiment Analysis with AI labels attitude, intensity & sarcasm probability for every tweet with AI. Use it when you need general sentiment on any topic. From $0.0003 per analyzed tweet.
• X (Twitter) Stock & Crypto AI Trading Signals labels bullish, bearish, neutral or mixed stance, content type, conviction & asset relevance with AI. Use it when you follow stocks, crypto or trading talk. From $0.0003 per analyzed tweet.
• X (Twitter) News Monitor with AI Analysis labels news posts by format, source attribution & topic relevance with AI. Use it when you separate reporting from commentary. From $0.0003 per analyzed tweet.
• X Tweet Viral Score Analyzer with AI estimates a Viral Score from 0 to 100 & a verdict for every tweet from 8 AI trait answers. Use it when you study why tweets spread or flop. From $0.0003 per analyzed tweet.

FAQ & support

Answers to common questions, then where to get help.

Do I need an AI account, X API key or login?

No. Xquik's X Tweet Classifier includes AI costs in its price. You need no AI account, tokens or key. You also need no X API key, login or credentials.

Do question versions matter?

Yes. Every answer stores the version you give its question. When you refine questions over time, you can tell which wording produced a result.

Why did a row come back with a failed or skipped analysis?

analysis.status is failed or skipped. The Actor collected & delivered the tweet, but the AI analysis did not complete. analysis.reason names the cause. context_limit means your context & targets leave no room for the tweet. service_unavailable means the analysis service was briefly unavailable. These rows carry no result charge. Shorten analysis.context or rerun the affected IDs.

The Actor still analyzes a tweet longer than maxContextBytes. It cuts quoted & replied-to posts first, then the tweet. analysis.contextAvailability.postText is then truncated. Raise maxContextBytes up to 64,000 to keep more text.

Does the analysis verify facts?

No. Answers describe what the post expresses & how the post frames it. Probabilities express AI confidence, not truth. Review important classifications against the original tweet, which every row keeps.

Which languages work?

Extraction supports every language X serves. We validate analysis on English customer scenarios first. Other supported languages return answers with the same structure. unclear categories & probabilities show uncertainty in every language.

How do I limit cost?

Filters, deduplication & maxItems run before analysis. You pay only for unique, filter-matching tweets. Use precise search operators, date bounds & engagement floors. Start with a small maxItems to check answer quality before a large run.

Is it legal to analyze X data?

The Actor requests public X fields. Results can contain personal data. Confirm a lawful purpose & follow applicable privacy rules. Ask qualified counsel when uncertain.

Can I use the API, schedules & integrations?

Yes. See the API tab for Python, JavaScript & cURL examples. Use Apify schedules for recurring runs. Pass the previous dataset ID as monitor.baselineDatasetId to see what changed. Apify integrations also connect runs to webhooks, Make, Zapier, n8n & Google Sheets.

Where do I get help?

Open an issue in the Issues tab with the run ID. Free diagnostics in the key-value store explain runs that need attention. A run that gets no row back says why in its status.