🔬Data Science: Text Mining (Definitions)

"The application of data mining techniques to discover actionable and meaningful patterns, profiles, and trends from documents or other text data." (Linda Volonino & Efraim Turban, "Information Technology for Management" 8th Ed, 2011)

"The process of evaluating unstructured text for patterns, extract actionable data and sentiment via semantic analysis, statistical methods, etc." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"Performing detailed full–text searches on the content of document." (Robert F Smallwood, "Managing Electronic Records: Methods, Best Practices, and Technologies", 2013)

"Data-mining techniques applied to text. Because these rely on the same underlying analytic approaches as text analysis, text mining is synonymous with text analysis, and the use of the term mining is primarily a matter of style and context." (Meta S Brown, "Data Mining For Dummies", 2014)

"Performing detailed full-text searches on the content of document." (Robert F Smallwood, "Information Governance: Concepts, Strategies, and Best Practices", 2014)

"It is the process of extracting information from textual sources, via their grammatical and statistical properties. Applications of text mining include security monitoring and analysis of online texts such as blogs, web-pages, web-posts, etc." (Hamid R Arabnia et al, "Application of Big Data for National Security", 2015)

"The analysis of raw data to produce results specific to a particular inquiry (e.g., how often a particular word is used, whether a particular product is in demand, how a particular consumer reacts to advertisements)." (James R Kalyvas & Michael R Overly, "Big Data: A Businessand Legal Guide", 2015)

"Performing detailed full-text searches on the content of document." (Robert F Smallwood, "Information Governance for Healthcare Professionals", 2018)

"The search and extraction of text, and its possible conversion to numerical data that is used for data analysis." (David Natingga, "Data Science Algorithms in a Week" 2nd Ed., 2018)

"The process of extracting information from collections of textual data and utilizing it for business objectives." (Gartner) 

📊Business Intelligence: Text Analytics (Definitions)

"A technique whereby software employs linguistics and pattern detection techniques to impute some larger meaning to the words in a document. Entity extraction and document categorization are two emerging types of text analytics." (Mike Moran & Bill Hunt , "Search Engine Marketing, Inc", 2005)

"Transforms unstructured text into structured 'text data' that can then be searched, mined, or discovered." (Linda Volonino & Efraim Turban, "Information Technology for Management 8th Ed", 2011)

"The process of analyzing unstructured text, extracting relevant information, and transforming it into structured information that can be leveraged in various ways." (Marcia Kaufman et al, "Big Data For Dummies", 2013)

"Refers generally to the process of deriving patterns and trends from unstructured content such as notes, reports, and comments." (Jim Davis & Aiman Zeid, "Business Transformation: A Roadmap for Maximizing Organizational Insights", 2014)

"The practice of analyzing unstructured data." (Brenda L Dietrich et al, "Analytics Across the Enterprise", 2014)

"Text analytics a variety of computer-based techniques designed to deriving information from text sources." (Hamid R Arabnia et al, "Application of Big Data for National Security", 2015)

"the process of analyzing unstructured text, extracting relevant information, and transforming it into structured information that can be leveraged in various ways." (Judith S Hurwitz, "Cognitive Computing and Big Data Analytics", 2015)

"The process of deriving insights from large volumes of text, typically through the use of specialized software to identify patterns, trends, and sentiment. " (Jonathan Ferrar et al, "The Power of People: Learn How Successful Organizations Use Workforce Analytics To Improve Business Performance", 2017)

[AI-based text analytics:] "Machine-learning and rules-based analytics technology that mines semistructured and unstructured text data sources and extracts structured information (such as keywords, concepts, entities, topics, sentiment, emotion, and intent) to analyze the findings for correlations, trends, outliers, patterns, and anomalies." (Forrester)

"A subset of natural language processing (NLP) technologies that identifies structures and patterns in text and transforms them into actionable insights to drive better business outcomes." (Forrester)

"Text analytics is the process of deriving information from text sources. It is used for several purposes, such as: summarization (trying to find the key content across a larger body of information or a single document), sentiment analysis (what is the nature of commentary on an issue), explicative (what is driving that commentary), investigative (what are the particular cases of a specific issue) and classification (what subject or what key content pieces does the text talk about)." (Gartner)