Text Analysis is a data interpreting process used to derive meaning from free text content. It works by using a combination of linguistic, statistical and machine learning techniques. Text Analysis parses the text to recognize patterns, interpret tone and sentiments, and define items based on context. The data drawn from the analysis helps deduct reasonable conclusions that would not easily be picked up by a reader. The first goal of Text Analysis is to create a classification system for unstructured text and make it manageable, understandable and retrievable. The second goal is to process the text through advanced interpretative techniques to understand context and language. Ultimately, it aims to turn subjective, raw input into meaningful and useful data.
Who uses Text Analysis?
Text Analysis is the primary method used by Security Companies to monitor and flag online plain text sources. Due to its ability to interpret intrinsic meaning of raw words, it can pick up on potential threats that may be hidden within text. This method is also used in the Biomedical Field to help scientific developments based on previous research findings. Text Analysis can index raw research, cluster data, extract relations and bring conclusions to light. Within the Retail Industry, Text Analysis is used to read customer sentiment and understand brand perception. It analyzes patterns and themes found in customer reviews and on social media to unlock meaning and create a measurable basis for decision making.
