Best Sentiment Analysis Tools

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Get insightful text analysis with machine learning that extracts, analyzes, and stores text. Train high-quality machine learning custom models without a single line of code with AutoML. Apply natural language understanding (NLU) to apps with Natural Language API. Use entity analysis to find and label fields within a document, including emails, chat, and social media, and then sentiment analysis to understand customer opinions to find actionable product and UX insights. Natural Language with speech-to-text API extracts insights from audio. Vision API adds optical character recognition (OCR) for scanned docs. Translation API understands sentiments in multiple languages. Use custom entity extraction to identify domain-specific entities within documents, many of which don’t appear in standard language models, without having to spend time or money on manual analysis. Train your own high-quality machine learning custom models to classify, extract, and detect sentiment.

Mine insights in unstructured text using NLP—no machine-learning expertise required—using text analytics, a collection of features from Cognitive Service for Language. Gain a deeper understanding of customer opinions with sentiment analysis. Identify key phrases and entities such as people, places, and organizations to understand common topics and trends. Classify medical terminology using domain-specific, pretrained models. Evaluate text in a wide range of languages. Identify important concepts in text, including key phrases and named entities such as people, events, and organizations. Examine what customers are saying about your brand and analyze sentiments around specific topics through opinion mining. Extract insights from unstructured clinical documents such as doctors' notes, electronic health records, and patient intake forms using text analytics for health.

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