What is Text Mining?
According to IBM, text mining is defined as the process of analyzing collections of textual data to recognize key concepts and themes as well as uncover hidden relationships and trends without knowing the precise terms or words that express those ideas. Additionally, each article of text requires linguistic based mining to return the desired concepts or information relating to them. Text mining tools can answer many of the following questions, such as, which ideas occur together, what they are linked to, what higher level categories are related, what the information predicts, as well as what behaviors can be expected.
Research has shown that nearly 80% of data exists as unstructured textual data. For this reason, text mining has become an important part of data analytics, attempting to determine the context surrounding the wealth of information that individuals leave across chats, social posts, reviews, surveys, call transcripts, customer emails, and news feeds among others. Through the advent of powerful, artificially intelligent tools that use machine learning and natural language processing for textual analysis, businesses are gaining additional value from information that would otherwise go unused.
A report published on Jisc in the UK reveals that accurate text analysis can reduce researcher or analyst work time by 70% through the proper techniques. The implementation of technological advances in text mining software will continue to provide companies a greater wealth of information from the previously unused information. As text mining becomes more accurate, businesses will gain greater insight into customer experience, product feedback, human resource management, and marketing understanding.
By increasing knowledge about the groups a business needs to focus on, they can increase productivity, protect their bottom line, and make adjustments in near real time by recognizing patterns in the data that otherwise would be hidden. Text mining can reveal unknown issues and pave the way for quick response by helping businesses understand the context behind the feedback. As unstructured text data grows in volume, text mining will become more and more important for deep understanding among businesses seeking value from their data.