Google Cloud Natural Language API
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.
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VizRefra
Analyze text with viztext 2D & 3D mapping text analysis topic modeling, sentiment analysis, word cloud. A unique machine learning algorithm to visualize topics in the text you want to discover. Text analysis provides topic modelling with navigation through 2D/ 3D maps. Uses referential framework to make logical relational topic analysis with zoom-in and zoom-out features on 2D and 3D maps including colorful word cloud. Analysis on the level of sentiment in the text with pie chart on ratio between positive, negative and neutral. Graphs top entities in the text with percentage as well as highlights in the text with entity type: government, person, organization, etc. Simple drag and drop, upload text file or paste text from the web or social media posts or enter HTTP address for a website that contains text article you like to analyze.
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WordStat
WordStat is a flexible and easy-to-use text analysis software – whether you need text mining tools for fast extraction of themes and trends, or careful and precise measurement with state-of-the-art quantitative content analysis tools. WordStat can be used by anyone who needs to quickly extract and analyze information from large amounts of documents. Our content analysis and text mining software can be used in many applications such as analysis of open-ended responses, business intelligence, content analysis of news coverage, fraud detection and more. WordStat‘s seamless integration with SimStat – our statistical data analysis tool – QDA Miner – our qualitative data analysis software – and Stata – the comprehensive statistical software from StataCorp, gives you unprecedented flexibility for analyzing text and relating its content to structured information, including numerical and categorical data.
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TextBlob
TextBlob is a Python library for processing textual data, offering a simple API to perform common natural language processing tasks such as part-of-speech tagging, noun phrase extraction, sentiment analysis, and classification. It stands on the giant shoulders of NLTK and Pattern, and plays nicely with both. Key features include tokenization (splitting text into words and sentences), word and phrase frequencies, parsing, n-grams, word inflection (pluralization and singularization) lemmatization, spelling correction, and WordNet integration. TextBlob is compatible with Python versions 2.7 and above, and 3.5 and above. It is actively developed on GitHub and is licensed under the MIT License. Comprehensive documentation, including a quick start guide and tutorials, is available to assist users in implementing various NLP tasks.
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