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. Xquik's X (Twitter) Stock & Crypto AI Trading Signals turns tweets into stances. Each stance is bullish, bearish, neutral or mixed, per ticker & coin. 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.

Read the stance behind stock, crypto & trading posts on X (Twitter). Xquik's X (Twitter) Stock & Crypto AI Trading Signals collects posts about your assets. It adds an AI-powered stance, content type, conviction level & asset relevance to every post. Separate firm calls from hedged remarks & analysis from promotion. Spot posts that use your asset's name for something else.

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

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

How to analyze market sentiment 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 $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. Start the run & 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

Conviction is 0 whenever the stance is neutral or unclear. A post without a direction cannot state one firmly. That answer puts all probability on level 0 & takes the stance's confidence.

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

Analyze your own text

Paste your own drafts, replies, reviews or notes in texts. Xquik's X (Twitter) Stock & Crypto AI Trading Signals analyzes them. 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.

How much does it cost to analyze market sentiment on X?

Xquik's X (Twitter) Stock & Crypto AI Trading Signals 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": "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 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 stance is bullish 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.

• cashtags counts stance per cashtag, such as $NVDA. Each asset's bullish ratio comes from choices.stance.
• Each cashtags entry adds signal with bullish & bearish counts. Its score runs from -1 to 1. The score is bullish minus bearish, divided by rows.
• The stance block adds the engagement-weighted split & the most engaged bullish & bearish posts.
• conviction reports the mean & the engagement-weighted mean.
• 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. It lists up to 50 changed rows.

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

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 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 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.

• 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 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) 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

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) Stock & Crypto AI Trading Signals 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 track several tickers in one run?

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

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.