Text mining algorithms are computational methods used to extract valuable information from unstructured text data. These algorithms analyze large volumes of text to identify patterns, trends, and relationships, enabling users to gain insights from sources like social media, news articles, and research papers. Common techniques in text mining include natural language processing (NLP), which helps machines understand human language, and sentiment analysis, which determines the emotional tone of a text. By applying these algorithms, businesses and researchers can make informed decisions based on the insights derived from textual data.