Dose My Opinion Count? A CNN-LSTM Approach for Sentiment Analysis of Indian General Elections
Ning Zhang, Jize Xiong, Zhiming Zhao, Mingyang Feng, Xiaosong Wang, Yuxin Qiao, Chufeng Jiang · Journal of Theory and Practice of Engineering Science · 2024
Sentiment analysis on social media platforms is a critical area of research for understanding public opinion, particularly during significant events like elections. This paper presents a sentiment analysis study using datasets from Reddit. Traditional sentiment analysis methods, while useful, often struggle with the informal and diverse nature of social media language, including sarcasm and contextual nuances. To address these challenges, we explore the use of a hybrid Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) model. This CNN-LSTM approach leverages the strengths of both architectures, capturing local features and contextual dependencies in the text. Our study aims to enhance sentiment classification accuracy and demonstrate the efficacy of the CNN-LSTM model in processing large-scale social media datasets.