![]() ![]() Organizations may assess customer reviews or social media posts to identify how often they use certain words that may relate to products, services or personal preferences and values. Here are some examples of text analysis methods and their applications: Word frequenciesĪ common text analysis method is to have the computer program identify how frequently certain words appear in a body of text. Some methods of text analysis may be more effective in gaining insight into some types of data than others. Organizations can apply text analysis techniques using different methods depending on their goals. Some information organizations may look to learn can include:Ĭustomer interests, values and preferencesĬompetitor activities, like their marketing strategies and customer engagementīrand monitoring and public relations based on company reputationĬustomer service requests, common questions and service challenges By using computer programs to convert unstructured linguistic data into computer-readable formats, organizations can use software to conduct detailed analyses and gain insight into their target customers. Since natural language, or the language that humans use in their speaking and writing, comprises unstructured data, machines can't interpret the meaning of the language without translating it into machine-readable code. This means that organizations can extract information from data that computers can't otherwise read. Text analysis is important because it allows computer programs to convert data written in non-computer languages into forms that data processing programs can interpret. Related: A Guide to Natural Processing Language Importance of text analysis A text analysis program can analyze the comment, compare it to other comments and identify linguistic patterns. For example, a customer leaving a text-based product review on a company's website is unstructured data because the reviewer's words don't follow the pre-determined structures and patterns of a computer-readable language, like code. ![]() In computer science, unstructured data refers to information that either doesn't have a pre-defined data model or doesn't have a defined organizational structure. ![]() Text analysis is a method by which a computer program extracts information from unstructured data and converts it into a form that computers can interpret. In this article, we define what text analysis is, explain its importance, describe analysis methods and outline the steps for how to do a text analysis. Learning about text analyses, what they are, how they work and why they're important can help you apply these techniques in the workplace. With text analysis, an organization uses a machine learning program to collect data from various digital platforms, assess that data and apply the analysis to gain insight into the text's meaning. Text analysis is an important tool that businesses and other organizations can use to gather information from unstructured data. ![]()
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