Natural Language Processing and Text Mining with Python
Sujith Samuel Mathew, Mohammad Amin Kuhail, Maha Hadid, Shahbano Farooq · 2025
Natural language processing (NLP) and Text Mining have emerged as key technologies for extracting meaningful information from unstructured text data, enabling organizations to automate the analysis and understanding of human language. It integrates linguistics and artificial intelligence (AI) concepts to comprehend and produce spoken and written language. This chapter is designed for those new to NLP and Text Mining, offering a simple guide on the initial steps of processing and analyzing text with Python. It explores the application of Python in NLP and Text Mining, highlighting its effectiveness in addressing challenges such as text preprocessing, topic modeling, and information retrieval. This chapter not only combines theoretical discussion but also provides practical examples to demonstrate how Python’s libraries facilitate textual data preprocessing, exploration, and modeling. The growing ecosystem of Python libraries like NLTK and Tweepy has enriched Python and made it one of the leading programming languages for implementing NLP and text-mining tasks. Python’s libraries’ flexibility and robust capabilities can significantly enhance the efficiency and effectiveness of NLP and Text Mining projects.