「sentiment」の検索結果

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。

Product review analysis and customer feedback intelligence. Pain point identification, praise pattern analysis, feature request extraction, sentiment analysis, and product improvement insights. Use when the user asks about review analysis, customer feedback, product reviews, or sentiment analysis.

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。

Orientação completa sobre conformidade com regulamentações do Banco Central do Brasil: Resolução CMN nº 4.893/2021 (Política de Segurança Cibernética), Resolução BCB nº 85/2021 (GRSIC), Open Finance Brasil (Resoluções BCB nº 32/2020 e atualizações), e demais normas prudenciais do BACEN. Cobre elaboração e revisão de Política de Segurança Cibernética, Plano de Ação e Resposta a Incidentes (PARI), Gestão de Riscos de Serviços de Informação e Comunicação (GRSIC), consentimento e compartilhamento de dados no Open Finance, requisitos de API, gestão de terceiros (outsourcing) e sanções do BACEN. Triggers: Bacen, Banco Central, CMN 4.893, Resolução 4.893, segurança cibernética bancária, PARI, GRSIC, Open Finance, Open Banking, compartilhamento de dados financeiros, consentimento Open Finance, API financeira, outsourcing bancário, risco cibernético, incidente cibernético banco, LGPD financeira, fintech compliance, instituição financeira, DICT, Pix segurança.

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。

Deep Amazon review analysis for competitive intelligence and product improvement. Extract sentiment patterns, recurring complaints, feature requests, and competitive insights from customer feedback. Turn reviews into actionable product development and marketing strategies. Use when the user asks about review analysis, customer feedback, product complaints, sentiment analysis, or what customers think about products.

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。

Brand monitoring and mention tracking via the Brand.dev API. Use when asked to monitor brand mentions, track sentiment, find PR opportunities, detect logo usage, or analyze brand presence online. Trigger phrases: "brand monitoring", "mention tracking", "brand sentiment", "PR opportunities", "logo detection", "brand.dev", "brand mentions", "media monitoring".

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。

Use when the user wants to monitor what is being said about the brand, competitors, and the category — channels and keywords to track, sentiment scoring, weekly and monthly listening reports, brand health metrics, early crisis detection, and content opportunities pulled from real conversations. Trigger on 'social listening', 'brand monitoring', 'sentiment analysis', 'what are people saying about us', 'track our mentions', 'monitor competitors online'. Also use when the user spotted a bad comment thread and wants to know if it is spreading. Not for — responding to a crisis already underway, see `66-crisis-playbook-global`; competitor strategy teardown, see `08-competitor-research-global`; auditing your own posts, see `39-content-audit-global`.

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 extraction from social media, news, and on-chain data including mention velocity, fear and greed indices, and influencer tracking

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。

When the user wants to monitor reviews, mentions, and community sentiment about their own product. Also use when the user mentions "track our reviews", "what are people saying about us", "brand monitoring", "reputation management", or "review alerts".

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.

AssemblyAI is a hosted speech-to-text API that transcribes audio and video files or live streams and adds speaker labels, sentiment, entity detection, PII redaction and LLM analysis of the transcript. Use when a user asks to transcribe a recording, label who said what, analyze call sentiment, redact personal data, stream live transcription, or summarize and question a transcript with LLM Gateway (the replacement for LeMUR).

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。

Fetch and analyze Amazon product reviews by ASIN, supporting 15 marketplaces (including US) with star rating filtering. Triggered when users mention Amazon reviews, US reviews, product reviews, buyer complaints, negative reviews, positive reviews, star ratings, review analysis, review sentiment, product improvement suggestions, Vine reviews, verified purchase reviews, competitor review research, Amazon reviews, US reviews, Amazon.com reviews, product feedback, negative review analysis, positive review analysis, star rating filter, review sentiment analysis, product improvement insights, Vine reviews, competitor reviews, customer feedback. Even if users do not explicitly say "reviews", this skill should be triggered whenever the task involves reading, filtering, or analyzing Amazon product customer 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。

Real-time quotes, K-line charts, order book, trade ticks, intraday capital flow, market sentiment temperature, trading session schedule, security lists, exchange rates, and IPO calendar for HK/US/A-share/SG via Longbridge. Also covers ADR premium and FX carry frameworks. Triggers: "股价", "行情", "K线", "走势", "盘口", "资金流", "市场温度", "汇率", "IPO", "打新", "隔夜股", "ADR溢价", "外汇套息", "K線", "盤口", "資金流", "市場溫度", "匯率", "ADR溢價", "外匯套息", "现在多少钱", "多少钱", "stock price", "quote", "kline", "chart", "depth", "orderbook", "capital flow", "market sentiment", "exchange rate", "IPO calendar", "security list", "ADR premium", "fx carry", "market open", "trading hours", "开市", "溢价", "NVDA.US", "700.HK", "600519.SH", "股價", "走勢", "開盤", "今天開市"

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。

Evaluates institutional flow patterns with fund flow analysis, positioning data, and sentiment indicator synthesis. Use when analyzing market flows, tracking institutional positioning, or assessing market sentiment.

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。

Customer feedback analysis — sentiment detection, NPS/CSAT frameworks, feature request clustering, support ticket triage, churn signal detection, and feedback-to-roadmap translation

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。

Use when analyzing published content (blog posts, social media, newsletters) for sentiment, structural quality, hook effectiveness, readability, topic classification, and engagement correlation. Invoke for daily post analysis, content audits, or engagement driver identification.

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.

Deep emotional sentiment analysis beyond positive/negative classification

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。

Multi-platform review analysis — pulls Yelp/Google/TripAdvisor reviews, identifies recurring complaints, sentiment patterns, response rate, and rating trajectory

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 CSAT, NPS comments, reviews, and support feedback for sentiment, recurring themes, customer pain, and service improvement actions. Use for customer support and CX feedback 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。

Analyze customer message text for sentiment, urgency, and emotional tone.

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。

Detect crisis signals in user content using NLP, mental health sentiment analysis, and safe intervention protocols. Implements suicide ideation detection, automated escalation, and crisis resource integration. Use for mental health apps, recovery platforms, support communities. Activate on "crisis detection", "suicide prevention", "mental health NLP", "intervention protocol". NOT for general sentiment analysis, medical diagnosis, or replacing professional help.

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", "TextAnalyticsClien...

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。

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。

Analyze meeting transcripts, recordings, and notes to extract action items, key decisions, topics, sentiment, and generate summaries using NLP and AI. Use when processing meeting transcripts, extracting action items, summarizing discussions, identifying key decisions, tracking topics and themes, analyzing sentiment, generating meeting notes, or building collaboration and productivity tools.

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。