{"enrichment":{"faq":[{"a":"Sentiment Analysis determines emotional tone in text through lexicon-based, machine learning, and deep learning approaches. It categorizes content as positive, negative, neutral, or mixed\u2014useful for understanding customer satisfaction, monitoring brand perception, and extracting insights from feedback.","q":"What does Sentiment Analysis do?"},{"a":"Yes. Sentiment Analysis classifies text sentiment to understand customer opinions and satisfaction. Its primary use (35% of intent weight) is categorizing customer-generated content\u2014reviews, comments, messages\u2014into positive, negative, neutral, or mixed sentiment buckets to gauge overall satisfaction levels.","q":"Can Sentiment Analysis classify text sentiment to understand customer opinions?"},{"a":"Sentiment Analysis monitors brand perception by analyzing feedback across channels over time, tracking how sentiment shifts. With 25% intent weight on trend monitoring, it enables you to spot emerging issues, measure campaign impact, and understand how customer opinions evolve\u2014critical for brand health assessment.","q":"How does Sentiment Analysis monitor brand perception and track sentiment trends?"},{"a":"Yes. Sentiment Analysis performs aspect-based sentiment analysis to extract sentiment about specific features or aspects of products. Rather than labeling entire reviews as positive or negative, it identifies which product elements (price, quality, design, support) customers praise or criticize.","q":"Can Sentiment Analysis extract sentiment about specific product features?"},{"a":"Sentiment Analysis uses lexicon-based methods, machine learning classifiers, and deep learning models for opinion extraction and classification. Lexicon approaches match words against sentiment dictionaries; ML models learn patterns from labeled data; deep learning captures complex semantic relationships in text.","q":"What approaches does Sentiment Analysis use for opinion mining?"},{"a":"Yes. Sentiment Analysis is released under the MIT license, allowing free use, modification, and distribution for both commercial and private projects with minimal restrictions.","q":"Is Sentiment Analysis available under an open-source license?"}],"shadow_tags":["text-classification","emotion-detection","opinion-mining","nlp-processing","feedback-analytics","brand-intelligence","social-listening","aspect-extraction","polarity-scoring","review-analysis"],"summary_rewrite":"Sentiment Analysis determines emotional tone in text through lexicon-based, machine learning, and deep learning approaches. It categorizes content as positive, negative, neutral, or mixed\u2014useful for understanding customer satisfaction, monitoring brand perception, and extracting insights from feedback."},"files":[{"bytes":11446,"path":"skills/sentiment-analysis/SKILL.md","sha256":"9b95fd4802f23b4c4ad04915fec568e91fe48f6286068419b1fd9ab3f774ff29","url":"https://skillfed.io/files/aj-geddes/useful-ai-prompts/sentiment-analysis/e5f14960/SKILL.md"}],"id":"aj-geddes/useful-ai-prompts/sentiment-analysis","links":{"html":"https://skillfed.io/aj-geddes/useful-ai-prompts/sentiment-analysis","md":"https://skillfed.io/aj-geddes/useful-ai-prompts/sentiment-analysis.md","repo":"https://github.com/aj-geddes/useful-ai-prompts"},"meta":{"agents_supported":[],"first_seen":"2026-07-28","forks":45,"language":"Shell","last_updated":"2026-03-04","license":"MIT","name":"Sentiment Analysis","publisher":"aj-geddes","stars":299},"relations":{"similar":[{"id":"langchain-ai/deepagents/data-visualization"},{"id":"aj-geddes/useful-ai-prompts/natural-language-processing"},{"id":"aj-geddes/useful-ai-prompts/feature-engineering"},{"id":"aj-geddes/useful-ai-prompts/regression-modeling"},{"id":"aj-geddes/useful-ai-prompts/ml-model-explanation"},{"id":"datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/5000-projects-analysis"},{"id":"aj-geddes/useful-ai-prompts/ab-test-analysis"},{"id":"aj-geddes/useful-ai-prompts/cohort-analysis"},{"id":"aj-geddes/useful-ai-prompts/anomaly-detection"},{"id":"aj-geddes/useful-ai-prompts/model-hyperparameter-tuning"}]},"slug":{"owner":"aj-geddes","repo":"useful-ai-prompts","skill":"sentiment-analysis"},"version":"e5f14960"}