AI Driven Sentiment News Curation
Devaraj F. V, Nagadeepa S. M, Neha B. Nanjegowda, Rakshitha D. H · International Journal for Research in Applied Science and Engineering Technology · 2025
Abstract- This paper provides an in-depth review of sentiment analysis techniques applied in various domains, focusing on methodologies such as the VADER sentiment analysis model and Long Short-Term Memory (LSTM) networks. The survey discusses their respective advantages, including VADER's efficiency in handling real-time and news articles text and LSTM's ability to capture long-term dependencies in sequential data. Additionally, the paper explores the use of Bidirectional LSTM (BiLSTM) for improving sentiment classification accuracy and the Natural Language Toolkit (NLTK) for enabling diverse natural language processing tasks.