X (Twitter) News Monitor 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) News Monitor sorts news posts by format, source attribution & relevance. 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.

Sort news posts on X (Twitter) by type & keep the original tweet data. Xquik's X (Twitter) News Monitor with AI Analysis collects posts about your topics. It adds an AI-powered format, source attribution & relevance answer to every post. Separate reporting from commentary & speculation. See whether a post names or links a source. Keep only posts about the organizations, people or topics you track.

• Format. It tells reporting, commentary, speculation, promotion & satire apart.
• Attribution. It shows whether a claim names a source, links one, is firsthand or has none.
• Relevance. It tells posts about your targets apart from namesakes.
• Complete source records. Every row keeps every field the tweet exposes, including linked articles when available.

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

How to classify news posts on X

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 search terms such as Nvidia earnings lang:en -filter:retweets, news account handles or tweet IDs.
2. Set maxItems & extraction filters such as date bounds, filter:links or minimum reposts.
3. Put the organizations, people or topics you track under analysis.targets, with aliases. Narrow the topic in analysis.context.
4. Start the run & open the dataset.

{
  "searchTerms": ["Nvidia earnings lang:en -filter:retweets"],
  "maxItems": 300,
  "analysis": {
    "targets": [{ "name": "Nvidia", "aliases": ["NVDA", "Jensen Huang"] }],
    "context": "Financial & product news about the chip maker."
  }
}

What the Actor answers

• Format is reporting, commentary, speculation, promotion, satire, unrelated or unclear.
• Attribution is named, linked, firsthand, absent or unclear.
• Relevance is the probability that the reported event concerns your targets.

Classification does not verify facts. Naming a source does not make it credible. Attribution describes what the post presents.

Analyze your own text

Paste your own drafts, replies, reviews or notes in texts. Xquik's X (Twitter) News Monitor analyzes them. It fetches nothing from X.

{
  "texts": [
    "Central bank holds rates at 4.5%, signals 2 cuts next year.",
    "I was at the port this morning. Cranes are idle & trucks are queued."
  ]
}

• 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 news posts on X?

Xquik's X (Twitter) News Monitor 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": "2100673144985993441", "text": "…", "retweetCount": 40 },
  "analysis": {
    "status": "succeeded",
    "answers": [
      {
        "questionId": "format",
        "type": "choice",
        "value": "reporting",
        "confidence": 0.9
      },
      {
        "questionId": "attribution",
        "type": "choice",
        "value": "named",
        "confidence": 0.84
      },
      { "questionId": "relevance", "type": "probability", "probability": 0.98 }
    ]
  }
}

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.

When a post links an X Article, the analysis also fetches that article. It adds the title, preview & text blocks as context. analysis.contextAvailability.article reports text_blocks, summary or not_supplied. summary means the title & preview only.

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 format is reporting in 4 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.

• The format split separates reporting from commentary, speculation, promotion & satire.
• attribution counts named, linked, firsthand & absent sources.
• relevance counts posts about each target.
• targets gives mentions per target. Each target's top lists its most engaged posts per answer category.
• Each targets entry has choices, the format & attribution split for posts about that target.
• sourceDomains counts linked domains across the run.
• monitor.changedRows lists posts whose decisions moved since the baseline.
• 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.

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 format, attribution or relevance decision 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 targets, context & the overview dataset view. Edit the search or targets before running.

• Classify Nvidia news posts on X
• Classify X Article news posts
• Classify OpenAI news posts on X
• Classify Apple news posts on X
• Classify Tesla news posts on X
• Classify SpaceX news posts on X
• Classify Boeing news posts on X
• Classify Pfizer news posts on X
• Classify Moderna news posts on X
• Classify ExxonMobil news posts on X
• Classify Federal Reserve news posts on X
• Classify European Central Bank news posts on X
• Classify Bank of England news posts on X

The remaining tasks cover more brands, topics & markets 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 Tweet Classifier with AI Analysis answers your own category, score & yes/no questions for every tweet with AI. Use it when the preset analyses do not fit your labels. 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 (Twitter) News Monitor includes AI costs in its price. You need no AI account, tokens or key. You also need no X API key, login or credentials.

Can I use my own questions?

Yes. Custom analysis.questions replace the defaults. Send 1 to 8 choice, score or probability questions. Choice questions accept 2 to 255 categories. Score questions need at least 2 ordered levels. Keep the same questions across runs you want to compare.

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.