Text Mining and Sentiment Analysis Using Big Data Techniques

The rapid pace of technological advancement and widespread use of internet-connected devices have led to a dramatic increase in both the volume and diversity of data collected daily. The term "Big Data" often describes this occurrence. Better decision-making is possible in many domains thanks to the many Text Mining approaches that allow for the extraction of valuable insights from data. Data, models, patterns, and trends may be found and used via these instruments. The underlying feelings and points of view in this data may be discovered and understood with the help of Sentiment Analysis. Using Twitter data as its basis, this research presents a proposed framework for text mining and sentiment analysis. In real-time, the system may collect, store, modify, and analyze data. The usefulness of Sentiment Analysis is shown by the creation of practical applications that use real-world events. Each technology and approach utilized for Text Mining and Sentiment Analysis may be validated using the supplied example case.