Text Data
Text data refers to unstructured or semi-structured information composed of human-readable characters, such as words, sentences, and paragraphs, often found in documents, emails, social media posts, and web content. It is a fundamental type of data in computing that requires specialized processing techniques like natural language processing (NLP) and text mining to extract meaningful insights, patterns, or structured information. Handling text data involves tasks such as tokenization, sentiment analysis, entity recognition, and language modeling.
Developers should learn about text data when working on applications involving language understanding, content analysis, or information retrieval, such as chatbots, search engines, recommendation systems, and automated customer support. It is essential for fields like data science, machine learning, and artificial intelligence, where processing large volumes of textual information enables tasks like sentiment detection, topic modeling, and text classification to drive business decisions or enhance user experiences.