Every day huge amount of text is generated online in vast quantities about the things happening in the world and in the minds of people. In order to generate meaningful business insights for organizations and analysts, the invaluable text data has to be mined. Extracting insights from unstructured text is costly and time consuming. Businesses use text classification to structure data in a fast and cost-efficient way to enhance decision making and automate processes. Text classification is a process of assigning tags according to the content with broad applications in sentiment analysis, spam detection, topic labeling and intent detection. This paper reviews the various text classification algorithms and their applications.

Text classification, sentiment analysis, tags, spam detection, topic labeling, intent detection

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