Extractive summarization is a technique in natural language processing that involves selecting and compiling key sentences or phrases from a text to create a concise summary. This method focuses on identifying the most important parts of the original content without altering the wording, ensuring that the summary retains the original meaning. The process typically uses algorithms to analyze the text and determine which sentences carry the most weight based on factors like frequency of important terms and sentence position. Extractive summarization is commonly used in applications such as news aggregation, academic research, and document summarization.