X (Twitter) Stock & Crypto AI Trading Signals | $0.0003/Tweet

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Xquik is the world's fastest & cheapest X (Twitter) scraper service with the most complete X data. X (Twitter) Stock & Crypto AI Trading Signals turns tweets into bullish, bearish, neutral or mixed stances per ticker & coin. Every other Apify Actor charges before filtering or deduplicating. Xquik charges only for delivered, unique, filter-matching results. AI costs are included in the per-tweet price. You pay no AI provider, buy no tokens & bring no key.

Read the stance behind stock, crypto & trading posts on X (Twitter) & keep the original tweet data. X (Twitter) Stock & Crypto AI Trading Signals collects posts about your tickers or assets. It then adds an AI-powered stance, content type, conviction level & asset relevance to every post. Separate firm calls from hedged remarks, analysis from promotion, & posts about your asset from unrelated uses of its name.

• Stance per post. Each post is bullish, bearish, neutral, mixed or unclear.
• Content type tells analysis, news, trade ideas, promotion, humor & questions apart.
• Conviction separates firm calls & positions from hedged remarks.
• Relevance filters out unrelated uses of a ticker or company name.
• Complete source records for every field the tweet exposes.

How to analyze market sentiment on X

1. Add search terms such as $NVDA lang:en -filter:retweets, cashtag queries, profile handles or tweet IDs.
2. Set maxItems & extraction filters such as date bounds or minimum likes.
3. Put asset names, tickers & aliases under analysis.targets & describe the asset in analysis.context.
4. Run the Actor & open the dataset.

{
  "searchTerms": ["$NVDA lang:en -filter:retweets"],
  "maxItems": 500,
  "analysis": {
    "targets": [{ "name": "Nvidia", "aliases": ["NVDA", "$NVDA"] }],
    "context": "The chip maker as a listed stock."
  }
}

What the Actor answers

Question	Answer
Stance	Bullish, bearish, neutral, mixed or unclear
Content	Analysis, news, trade, promotion, humor, question or unclear
Conviction	0 hedged remark, 1 stated view, 2 firm call or position
Relevance	Probability that the post treats your targets as assets

Answers describe what authors express. They are not investment advice & do not verify claims, prices or filings.

Analyze your own text

Paste your own text in texts: drafts, replies, reviews or notes. The Actor analyzes it & fetches nothing from X.

{
  "texts": [
    "$NVDA guidance beat again. I am adding on any dip below 900.",
    "Not touching $BTC until the ETF flows turn positive."
  ]
}

• 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.

Pricing

AI costs are included in the per-tweet price. You pay no AI provider, buy no tokens & bring no key.

From $0.0003 per successfully analyzed tweet, with no start fee. The price includes collection. The analysis allowance is 8 questions, 8,000 bytes per question definition & 12,000 bytes of context per tweet. Extraction filters & deduplication run before analysis, so filtered-out & duplicate rows are never analyzed or charged. Failed & skipped analyses & diagnostic rows have no result charge. Apify bills platform usage separately. The Pricing tab shows it.

Input & output examples

The input above is copy-ready. Output rows look like this (abbreviated):

{
  "tweet": { "id": "2100692112916574711", "text": "…", "likeCount": 31 },
  "analysis": {
    "status": "succeeded",
    "answers": [
      {
        "questionId": "stance",
        "type": "choice",
        "value": "bullish",
        "confidence": 0.86
      },
      {
        "questionId": "content",
        "type": "choice",
        "value": "analysis",
        "confidence": 0.79
      },
      {
        "questionId": "conviction",
        "type": "score",
        "value": 1,
        "confidence": 0.7
      },
      { "questionId": "relevance", "type": "probability", "probability": 0.95 }
    ]
  }
}

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

Each run writes an analysis-summary record to its key-value store & repeats it under results.analysisSummary in the run report. It counts analyzed, failed & skipped rows, sums engagement, and summarizes every question. cashtags counts stance per cashtag such as $NVDA, so the bullish ratio per asset comes from choices.stance. The stance block adds the engagement-weighted split & the most engaged bullish & bearish posts. conviction reports the mean & the engagement-weighted mean. The summary rounds numbers to 4 decimals. An empty run reports zero counts & null means. Each cashtags entry adds signal with a bullish count, a bearish count & a score from -1 to 1. The score is (bullish - bearish) / rows. monitor.changedRows lists tweets whose stance moved since the baseline. Every row lists sourceDomains, the hostnames it links to. With monitor.baselineDatasetId set, the summary's monitor block counts comparison statuses & lists up to 50 changed rows.

Every result row also carries answers, a flat map from question ID to the chosen category, score, or probability. The Flat answers dataset view & CSV or Excel exports show one column per question 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. Every row then gains a monitor object. Its status is 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 stance, content type or conviction level that moved from previous to current. Decisions compare by category, rounded score level, or yes/no at 0.5. A decision counts as changed in three cases. The earlier category falls below 0.4 probability. A score moves at least 0.6 levels. A yes/no probability lands at least 0.1 from the threshold. Near-tie jitter between runs stays unchanged. Baselines above maxBaselineRows (default 100,000) or from different settings stop the run before collection with a diagnostic row.

Task examples

Choose from 50 public tasks. Each starts from a real English search with a bounded maxItems, ready-made targets & context, & the overview dataset view. Edit the search or targets before running.

• Nvidia (NVDA) market sentiment on X
• Tesla (TSLA) market sentiment on X
• Apple (AAPL) market sentiment on X
• Amazon (AMZN) market sentiment on X
• Microsoft (MSFT) market sentiment on X
• Alphabet (GOOGL) market sentiment on X
• Meta (META) market sentiment on X
• AMD (AMD) market sentiment on X
• Palantir (PLTR) market sentiment on X
• Coinbase (COIN) market sentiment on X
• Strategy (MSTR) market sentiment on X
• Robinhood (HOOD) market sentiment 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 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 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 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 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) 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 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

Can I track several tickers in one run?

Yes. List every asset under analysis.targets with its tickers & aliases, & combine search terms. Relevance answers tell you which posts treat your targets as assets.

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

The Actor collected & delivered the tweet, but the AI analysis did not complete. analysis.reason names the cause, such as context_limit when the tweet & its context exceed maxContextBytes, or service_unavailable after retries. These rows carry no result charge. Raise maxContextBytes (up to 12,000) or rerun the affected IDs.

Does the analysis verify facts?

No. Answers describe what the post expresses & how the post frames it. Probabilities express model 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, so the Actor analyzes & charges only 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.

Where do I get help?

Open an issue on the Actor page or contact support@xquik.com with the run ID. Free diagnostics in the key-value store explain empty, partial or interrupted runs.

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