Definition
Text data mining is the process of extracting valuable insights and patterns from unstructured textual data using machine learning, natural language processing (NLP), and statistical analysis. It can improve decision-making, customer experience, product development, and business success.
Text Data Mining Applications
- Sentiment analysis is used to ascertain users’ opinions about a specific product, brand, or service based on their feedback, reviews, and social media posts.
- Topic modeling automatically identifies the themes or topics in texts such as research papers, customer feedback, and news articles.
- Text classification automatically classifies text data into predefined classes based on its content, including spam or non-spam emails or positive or negative reviews.
- Text summarization automatically generates a summary of multiple textual data, such as news articles, to offer a faster overview of the content.
- Named Entity Recognition automatically identifies and extracts named entities such as locations, people, and organizations from a text corpus.