Enhancing Sentiment Analysis of Movie Reviews with PySpark

Sentiment analysis is pivotal in the film industry as it provides insights into audience opinions, aids in recommending movies, and forecasts box office performance. This research utilizes Apache Spark’s PySpark framework to enhance sentiment analysis in movie reviews. Traditional sentiment analysis techniques often struggle with the large and complex nature of textual data in movie reviews. PySpark’s distributed computing capabilities enable efficient processing and analysis of extensive datasets. We employ logistic regression for classification and validate our model using standard metrics. Our method shows considerable improvements in processing speed and scalability, offering valuable insights into public sentiment and its potential effects on box office outcomes.