Text analysis software, also called text analytics or text mining software, helps users gain insights from both structured and unstructured text data using natural language processing (NLP). Such insights include sentiment analysis, key phrases, language, themes and patterns, and entities, among others. These solutions leverage NLP and machine learning to pull out these different insights and provide visual representations of the data for easier interpretation.
Text analysis tools can consume text data from a variety of sources, including emails, phone transcripts, surveys, customer reviews, and other documents. By importing text data from these different sources, businesses are better equipped to understand and analyze customer or employee sentiment, intelligently classify documents, and improve written content. Text analysis software may be used in conjunction with other analytics tools, including big data analytics and business intelligence platforms.
To qualify for the Text Analysis category, a product must:
Anderson Analytics is a market research firm to leverage text analytics and their patent pending SaaS Text Analytics platform OdinText can be used to quickly analyze unstructured data ranging from large scale VoC surveys to customer call center logs/emails or social media data.
Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text. Amazon Comprehend identifies the language of the text; extracts key phrases, places, people, brands, or events; understands how positive or negative the text is; and automatically organizes a collection of text files by topic.
Datumbox API offers a large number of off-the-shelf Classifiers and Natural Language Processing services which can be used in a broad spectrum of applications including: Sentiment Analysis, Topic Classification, Language Detection, Subjectivity Analysis, Spam Detection, Reading Assessment, Keyword and Text Extraction and more.
With dozens of powerful text analytics, data science, human coding, and machine-learning features, including instant access to the Gnip PowerTrack 2.0 for Twitter, historical Twitter, and the free Twitter Search API, DiscoverText provides cloud-based software tools to quickly evaluate large amounts of text, survey, and Twitter data.
IBM SPSS Text Analytics for Surveys software lets you transform unstructured survey text into quantitative data and gain insight using sentiment analysis. The solution uses natural language processing (NLP) technologies specifically designed for survey text.
Information Discovery is a leading text analytics and machine learning platform that allows you to get insights in your structured and unstructured data and explore important information in the most flexible way. Information Discovery collects and analyzes all kind of documents, such as patents, research literature, databases, websites, and other enterprise repositories
Intellexer Categorizer is a semantic tool that automatically classifies documents by content and organizes them within categories that best fit the structure of your company and processes. For example, the categories can be Human Resources, Research and Development, Finance, Customer Feedback, Newsletters, etc.
Intellexer Clusterizer enables effective organizing, normalizing, linking, and processing of documents, presenting of retrieval results in a more logical, structured, and searchable way. Meanwhile, it can provide information seekers with a means of browsing, and searching information efficiently in a user friendly format to fulfill the user's information need
Intellexer Linguistic Processor is used to parse the input text and to extract multiple kinds of relations, for example, syntactic (noun phrases, verb phrases, adjectival and adverbial phrases, etc.) and semantic (subject-verb-object; Color, Direction, Degree, Effectiveness, etc.) ones. The output of Linguistic Processor is a semantic tree with certain semantic types of relations assigned to the links between the sentence elements
Intellexer Named Entity Recognizer successfully identifies not only personal names, names of organizations and geographical locations, but also extracts such entities as positions/occupations, nationalities, dates, ages, durations and names of events. The results of the Intellexer Named Entity Recognizer can be of great value to information end-user industries of all kinds, especially banks, finance companies, publishers and governments.
Intellexer Preformator extracts plain text and information about the text layout from documents of different formats (doc, pdf, rtf, html, etc.). Also Preformator automatically determines the structure (patent, news or scientific article, review, etc.) of document and its theme (economics, law, sports, etc.).
Intellexer Sentiment Analyzer is a powerful and efficient solution that automatically extracts sentiments (positivity/negativity), opinion objects and emotions (liking, anger, disgust, etc.) from unstructured text information. Besides, Intellexer Sentiment Analyzer can be successfully used for document sentiment classification and review rating prediction tasks
Intellexer Summarizer receives a source document and passes it to the Intellexer Preformator which extracts plain text (along with text formatting information, headers, links, etc.), detects document structure and language (using Intellexer Language Recognizer). Extracted text is received to the Intellexer Linguistic Processor which provides syntactic and semantic processing. After complete analysis extracted information is passed back to the Intellexer Summarizer for document summary generation
Luminoso Analytics applies artificial intelligence (AI) and natural language understanding (NLU) to accurately analyze text-based data for any industry without lengthy setup time or training. Luminoso Analytics allows clients to easily upload, process, analyze, and visualize batches or streams of unstructured data. Compass can analyze any type text-based data, including open-ended survey responses, call transcripts, chatbot or live chat transcripts, product reviews, articles, emails, and NPS open-ends. Data can be processed natively in 13 languages, including Chinese, Korean, Japanese, and Arabic. Companies use Luminoso Analytics to surface key topics and concepts in data, uncover and monitor trends over time, dig into nuanced emotions and their root causes, and identify key differences across metadata. There are many ways customers utilize the insights that Analytics uncovers including brand monitoring, churn and retention analysis, issue detection and monitoring, and identifying root drivers of NPS scores to name a few. The product is flexible and can be deployed in standard or private Cloud or On-premise solution, or integrated into an end-to-end platform via the API.
NetOwl TextMiner is a powerful text mining solution that enables users to find, organize, analyze, and mine a large volume of unstructured information. TextMiner integrates state-of-the-art data analysis tools within a robust, scalable architecture. The user gains quick access to all and only high-value information by means of an innovative and easy-to-use Web-based interface that promotes the rapid navigation of large amounts of textual data. It is ideal for supporting 'what if' analysis, discovery, quick response investigation, and detailed research.
Apache OpenNLP library is a machine learning based toolkit for the processing of natural language text that supports the common NLP tasks, such as tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing, and coreference resolution these tasks are usually required to build more advanced text processing services and includes maximum entropy and perceptron based machine learning.
ITALASSI is a freeware program that has been written to facilitate interpretation of regression models (2 independent variables) with an interaction term. The program allows you to enter several regression models (two bivariate, one multiple additive, and one multivariate with interaction) in the form of equations or compute those equations from raw data and displays the various models using 2D and 3D graphs. The program may also be used in advanced stat courses to illustrate statistical interactions or applied multiple regression.
MVSP is an inexpensive yet powerful multivariate analysis program for PC compatibles that performs a variety of ordination and cluster analyses. It provides an easy means of analyzing your data in fields ranging from ecology and geology to sociology and market research. MVSP is in use at hundreds of sites in over 50 countries.
QDA Miner is an easy-to-use qualitative data analysis software package for coding, annotating, retrieving and analyzing small and large collections of documents and images. QDA Miner qualitative data analysis tool may be used to analyze interview or focus group transcripts, legal documents, journal articles, speeches, even entire books, as well as drawings, photographs, paintings, and other types of visual documents.
Simstat goes beyond mere statistical analysis. It offers output management features not found in any other program, as well as its own scripting language to automate statistical analysis and to write small applications, interactive tutorials with multimedia capabilities, as well as computer assisted interviewing systems
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.
Rosette® text analytics is a robust toolkit for processing language, documents, and names. When combined together, they create powerful solutions that deliver insights for better decisions and deeper value for their users. Our customers across the globe, in government, finance, eDiscovery, search, social media, and beyond, depend on Rosette text analytics to analyze massive volumes of data and transform their unstructured text.
SAP HANA offers an end-to-end solution for developing and deploying high-value predictive analytics and machine learning programs. The machine learning capabilities in SAP HANA enable data scientists and application developers to build, train, and manage machine learning models, where data is persisted.
With SAS Contextual Analysis, you can quickly derive insight from your text data by categorizing documents, extracting facts and understanding document sentiment – all from a single interface. You can also define rules without creating a training corpus.