Writing
Advanced AI Sentiment & Emotional Intelligence Analyzer
Deeply decode the tone, intent, and emotional subtext of any text with surgical precision.
#Communication#customer-service#sentiment analysis#linguistics
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Created by PromptLib Team
Published February 12, 2026
3,140 copies
4.5 rating
Act as an expert Linguistic Analyst and Sentiment Researcher. Your goal is to perform a deep-dive sentiment analysis on the following text: "[INPUT_TEXT]". Follow these specific instructions for your analysis: 1. **Core Sentiment**: Classify the overall sentiment as Positive, Negative, Neutral, or Mixed. Provide a confidence score from 0-100%. 2. **Emotional Profile**: Identify the top 3 emotions present (e.g., Frustration, Joy, Anxiety, Gratitude). Explain the linguistic triggers for each. 3. **Tone & Style**: Describe the tone (e.g., Professional, Sarcastic, Urgent, Defensive) and identify if the author's intent aligns with their word choice. 4. **Subtext & Nuance**: Detect any underlying sarcasm, irony, or passive-aggressiveness that a basic algorithm might miss. 5. **Key Phrases**: Extract the specific quotes or keywords that most heavily influenced your analysis. 6. **Communication Advice**: If the user needs to respond to this text, suggest the optimal [RESPONSE_TONE] to achieve a [DESIRED_OUTCOME]. Please present your findings in a structured report format with clear headings.
Act as an expert Linguistic Analyst and Sentiment Researcher. Your goal is to perform a deep-dive sentiment analysis on the following text: "[INPUT_TEXT]". Follow these specific instructions for your analysis: 1. **Core Sentiment**: Classify the overall sentiment as Positive, Negative, Neutral, or Mixed. Provide a confidence score from 0-100%. 2. **Emotional Profile**: Identify the top 3 emotions present (e.g., Frustration, Joy, Anxiety, Gratitude). Explain the linguistic triggers for each. 3. **Tone & Style**: Describe the tone (e.g., Professional, Sarcastic, Urgent, Defensive) and identify if the author's intent aligns with their word choice. 4. **Subtext & Nuance**: Detect any underlying sarcasm, irony, or passive-aggressiveness that a basic algorithm might miss. 5. **Key Phrases**: Extract the specific quotes or keywords that most heavily influenced your analysis. 6. **Communication Advice**: If the user needs to respond to this text, suggest the optimal [RESPONSE_TONE] to achieve a [DESIRED_OUTCOME]. Please present your findings in a structured report format with clear headings.
Best Use Cases
Analyzing customer support tickets to prioritize angry users.
Evaluating marketing copy to ensure it hits the right emotional notes.
Interpreting ambiguous internal Slack messages or emails.
Reviewing social media mentions for brand reputation management.
Checking your own drafts to ensure you don't sound accidentally aggressive.
Frequently Asked Questions
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Estimated time:8 min
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