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For any company to survive in this era, getting vital data about its customers and other stakeholders through text analytics is a must. When there is no dearth of structured and unstructured data about an organization , it is useless unless it is analyzed to provide the fan database information needed for decision making. This is where text analytics and text mining tools come into play. Text analytics software enables you to find patterns and trends in raw text data and provide you with statistical models. Before we dive into the details of text analytics tools, let us understand the text analytics technology and its applications.
Contents hide
1 What is text analysis and mining?
2 Examples of Using Text Analysis and Mining Software
2.1 Fast interpretation of large documents
2.2 Understanding Employee Feedback
3 Amazon Comprehend
4 Thematic
5 Google Cloud NLP
6 Chattermill
7 Voyant Tools
8 MonkeyLearn
9 Keatext
10 WordStat
11 RapidMiner
12 Conclusion
12.1 Related publications:
What is text analysis and mining?
Text analysis is the process of gathering meaningful insights from raw text data. It means extracting user sentiment and valuable data from customer opinions and reviews to make informed decisions. Text analysis is an umbrella term used to refer to activities that include text extraction, identification, categorization, parsing, entity relationship modeling , and clustering. Although data analysis and data mining are different fields of study, these terms are currently used interchangeably as both refer to data collection using different statistical approaches. Text analysis provides qualitative insights into customer reviews by identifying sentiment in any free-form text. On the other hand, text analysis uses machine learning and NLP technologies to gather insights from structured data.
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