Natural Language Processing in the Era of BIG DATA

Natural Language Processing (NLP) has become a revolution in the age of big data. The large and diverse vocabulary generated by big data makes it possible to develop advanced NLP models using machine learning algorithms and distributed computing techniques. The combination of NLP and big data has led to the emergence of powerful language models such as BERT and GPT, allowing NLP to better understand content and provide insights in many applications such as thinking, machine translation, response and custom NLP text. The application of NLP in the big data environment provides solutions to many problems in industries. Business intelligence can benefit from collecting data and providing real-time insights, while collaboration can be enhanced through networking. Sentiment analysis helps improve product and market research by allowing organisations to understand customers’ thoughts and preferences.This study demonstrates the effectiveness of NLP in analysing large datasets, especially for sentiment analysis using the Map Reduce framework. Overall, this paper highlights the potential and challenges of integrating NLP with Big Data and gives insight into how the combination works. This power can be used in many ways, leading to a better understanding of language and data analysis.