「sentiment」の検索結果

Sentiment & Momentum Analysis — news sentiment scoring, social media buzz (Reddit/StockTwits/X), analyst ratings consensus, institutional 13F activity, insider trading signals, and short interest / squeeze potential. Returns Sentiment Score (0-100). Triggered by "trade sentiment <TICKER>".

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Analyze cryptocurrency market sentiment using Fear & Greed Index, news analysis, and market momentum. Use when gauging overall market mood, checking if markets are fearful or greedy, or analyzing sentiment for specific coins. Trigger with phrases like "analyze crypto sentiment", "check market mood", "is the market fearful", "sentiment for Bitcoin", or "Fear and Greed index".

日本語の概要は準備中です。原文の説明を表示しています。

Amazon niche market review analysis and consumer sentiment insights. Trigger when the user mentions niche market review analysis, consumer sentiment, user pain points, customer feedback insights, review topic analysis, positive/negative review breakdown, niche market opinion mining, product review sentiment analysis, niche market reviews, consumer sentiment, customer pain points, review topic analysis, positive/negative reviews, opinion mining, Nexscope data. Even if the user does not explicitly mention "niche market reviews", if their need involves analyzing consumer reviews within Amazon niche markets or understanding customer sentiment at the niche market level, this skill should also be triggered.

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"Implement VADER sentiment analysis for social media text scoring. Use this skill when the user needs to analyze sentiment in tweets, reviews, or social posts, compute compound sentiment scores, or classify text polarity — even if they say 'is this positive or negative', 'sentiment of these comments', or 'social media mood analysis'.".

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Analyze brand or topic sentiment across Twitter, Reddit, and Instagram using Xpoz. Classifies posts as positive/neutral/negative, extracts recurring themes, and generates a sentiment report. Use when asked for "sentiment analysis", "what are people saying about X", "brand sentiment", or "social media opinion on X".

日本語の概要は準備中です。原文の説明を表示しています。

Analyze brand or topic sentiment across Twitter, Reddit, and Instagram using Xpoz. Classifies posts as positive/neutral/negative, extracts recurring themes, and generates a sentiment report. Use when asked for "sentiment analysis", "what are people saying about X", "brand sentiment", or "social media opinion on X".

日本語の概要は準備中です。原文の説明を表示しています。

Sentiment & Momentum Analysis Agent — news sentiment, social media buzz, analyst ratings, institutional activity, insider trading, and short interest with Sentiment Score (0-100)

日本語の概要は準備中です。原文の説明を表示しています。

Earnings sentiment analysis, analyst estimates vs guidance, earnings surprise history, consensus sentiment, earnings revision trends, analyst rating changes, earnings beat miss track record, guidance accuracy, whisper numbers, pre-announcement sentiment

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Analyze sentiment in any text — reviews, social posts, feedback, or articles. Returns sentiment polarity (positive, negative, neutral), confidence score, and key phrases driving the sentiment. Useful for brand monitoring, customer feedback analysis, and content evaluation.

日本語の概要は準備中です。原文の説明を表示しています。

Crypto Sentiment Analysis Agent — social media buzz, news tone, community health, developer activity, narrative momentum, and Fear & Greed Index with Sentiment Score (0-100)

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X/Twitter public sentiment research for recent market, company, product, or community discourse. Use when the brief asks what people are saying on X, Twitter sentiment, CT sentiment, public opinion, expert posts, or social reaction around a stock, sector, company, product, or market event.

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Analyze user feedback data to identify segments with sentiment scores, JTBD, and product satisfaction insights. Use when analyzing user feedback at scale, running sentiment analysis on reviews or surveys, or identifying satisfaction patterns.

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Fetch normalized stock sentiment across Reddit, X.com, financial news, and Polymarket from the Adanos Finance API: buzz score, bullish percentage, mention or trade counts, and trend. Use this skill whenever the user asks how much a stock is being discussed or how hot it is on social platforms, how many Reddit mentions or Polymarket bets a company has, whether Reddit, X, and news agree, or wants to compare stock buzz and sentiment across tickers. Read-only: it never places trades or modifies anything.

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Analyze finance text sentiment using FinBERT or LLM. Use when the user needs to determine the sentiment (positive/negative/neutral) and score of financial text markets.

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Execute this skill enables AI assistant to analyze the sentiment of text data. it identifies the emotional tone expressed in text, classifying it as positive, negative, or neutral. use this skill when a user requests sentiment analysis, opinion mining, or emoti... Use when analyzing code or data. Trigger with phrases like 'analyze', 'review', or 'examine'.

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Get recent news and sentiment for a stock. Use when user asks about news, headlines, sentiment, what's happening with a stock, or recent developments.

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X/Twitter public sentiment research. Searches X for real-time perspectives, market sentiment, expert opinions, breaking news, and community discourse. Use when: user asks "what are people saying about", "X/Twitter sentiment", "check X for", "search twitter for", "what's CT saying about", or wants public opinion on a stock, sector, company, or market event.

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Comprehensive social media operations for B2B SaaS brand building and engagement. Use this skill to develop LinkedIn strategy, decide whether to run a LinkedIn newsletter and how to scope it, capture consented registrations from LinkedIn Events, check LinkedIn Live eligibility, manage Twitter/X presence, create YouTube content, engage on Reddit communities, decide whether and how to answer on Quora, build community, develop influencer and creator partnerships, vet a creator before paying them, start or fix a B2B podcast, book podcast guests and guest appearances, judge whether a podcast is worth appearing on when you cannot audit its numbers, write show notes and transcripts, run social listening (what are people saying about us, share of voice, brand monitoring, validated sentiment, alert thresholds, routing signals to the right owner), and execute organic social campaigns. Also triggers on: LinkedIn, LinkedIn newsletter, LinkedIn Events, LinkedIn Live, event registration form, subscribe to our newsletter on LinkedIn, marketing consent checkbox, Notify Employees, Twitter/X, YouTube, Reddit, community, influencer, creator partnerships, influencer vetting, engagement rate, fake followers, engagement pods, FTC disclosure, sponsored post disclosure, media kit, social media strategy, organic social, employee advocacy, podcast, podcast strategy, podcast guesting, how do I know if this podcast has real listeners, the host says they get 50k downloads, is this podcast worth going on, podcast RSS feed research, IAB podcast measurement certification, Listen Score, Apple Podcasts reviews, show notes, audiogram, episode transcript, social media account access, who has admin on our LinkedIn page, the person who ran our social accounts left, locked out of our company account, social media offboarding, YouTube channel owner, Slack primary owner, social account MFA, social media approval workflow, pause all scheduled posts, social listening, what are people saying about us, brand monitoring, brand mentions, share of voice, social share of voice vs competitors, sentiment analysis, is our sentiment dashboard accurate, listening query, boolean query, mention alerts, spike alert, CrowdTangle replacement, Reddit API access, which platforms can our listening tool see, someone on Reddit asked for a tool like ours, comment mining, voice of customer from social.

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Trustpilot customer reviews scraper for any company listed on trustpilot.com — given a company domain (e.g. shopify.com, apple.com, shopwagandtail.com) plus optional filters (page number, single star rating 1-5, single language ISO code, verified-only flag, has-company-reply flag, date period last30days/last3months/last6months/last12months, free-text keyword search, and reviewer countryCode client-side filter), extracts paginated reviews with 20+ fields per review: reviewId, reviewUrl, reviewTitle, reviewDescription, reviewRatingScore (1-5), reviewDate (ISO publishedDate), reviewDateOfExperience, reviewLabel, isReviewVerified, reviewer (display name), reviewerId, reviewersCountry (ISO Alpha-2), reviewLanguage, reviewCompanyResponse (the company reply text), plus pagination metadata (currentPage, totalPages, totalCount). Optional flags add reviewer profile metadata (reviewerNumberOfReviews, reviewerProfileIsVerified), reply analysis dates (companyReplyPublishedDate, companyReplyUpdatedDate), extended metadata (reviewSource, reviewVerificationSource, reviewLikes), and review photos. Use when user mentions Trustpilot reviews, scrape Trustpilot, get reviews from Trustpilot, Trustpilot review scraper, Trustpilot customer reviews, extract Trustpilot reviews, Trustpilot review data, download Trustpilot reviews, paginate Trustpilot, paginated Trustpilot reviews, filter Trustpilot reviews by star, filter Trustpilot by language, verified reviews Trustpilot, has reply Trustpilot, company response Trustpilot, Trustpilot reply analysis, brand monitoring Trustpilot, sentiment analysis Trustpilot, competitor reviews Trustpilot, bulk reviews from a Trustpilot page, batch download reviews, trustpilot.com reviews scraping, fake review research Trustpilot, Trustpilot dataset, persona research from Trustpilot reviews, Trustpilot keyword search reviews, Trustpilot date range reviews, review export Trustpilot. Also applies to comparing review trends across competitors, training data for LLM sentiment classifiers, monitoring competitor response time, exporting reviews for BI dashboards, lead generation from active reviewers, ML / fake-review detection, and aggregator sites that display third-party reviews.

日本語の概要は準備中です。原文の説明を表示しています。

Walmart product reviews scraper: given a walmart.com product item ID, navigate to the reviews page and extract paginated customer reviews including reviewId, rating, title, review text, author nickname, submission date, verified purchase status, helpful votes, variant selected (color/size), badges, fulfilled by, seller name, and photo count. Use when user mentions walmart reviews, walmart product reviews, walmart customer reviews, scrape walmart reviews, extract walmart reviews, walmart review scraper, walmart ratings and reviews, walmart review data, walmart review text, walmart review pagination, get reviews from walmart, walmart review collector, walmart verified purchase reviews, walmart review analysis, walmart sentiment analysis, walmart review export, walmart buyer feedback. Also applies to bulk collection of walmart product reviews across multiple items, sentiment analysis on walmart reviews for market research, competitor product review benchmarking on walmart, and monitoring new walmart reviews over time.

日本語の概要は準備中です。原文の説明を表示しています。

Market Sentiment reference method. Use when studying this focused method, not to run an API request. External API-key access for its legacy endpoints is not published in this release.

日本語の概要は準備中です。原文の説明を表示しています。

Azure AI Text Analytics SDK for sentiment analysis, entity recognition, key phrases, language detection, PII, and healthcare NLP. Use for natural language processing on text. Triggers: "text analytics", "sentiment analysis", "entity recognition", "key phrase", "PII detection", "TextAnalyticsClient".

日本語の概要は準備中です。原文の説明を表示しています。

Comprehensive market environment analysis and reporting tool. Analyzes global markets including US, European, Asian markets, forex, commodities, and economic indicators. Provides risk-on/risk-off assessment, sector analysis, and technical indicator interpretation. Triggers on keywords like market analysis, market environment, global markets, trading environment, market conditions, investment climate, market sentiment, forex analysis, stock market analysis, 相場環境, 市場分析, マーケット状況, 投資環境.

Use when the user asks to "track our share of voice", "what share of the conversation do we own vs competitors", or "trend our SOV this quarter"; computes SOV% = brand mentions ÷ (brand + competitor panel mentions) per platform per period on a LOCKED competitor panel — a panel switch invalidates the trend (restart the series and log the break; the ECHO O3 rule) — plus a sentiment-weighted SOV variant (sentiment labeled Estimated unless human-coded) and a Wikipedia-pageviews attention-share alternative; built from keyless listening connectors, gdelt.py news echo, and user exports — public counts only, closed platforms are never scraped. Not for backlink or offsite SEO signals — use offsite-signal-analyzer. 声量份额/竞品声量对比/提及份额/注意力份额

日本語の概要は準備中です。原文の説明を表示しています。