Team Error Point at BLP-2023 Task 2: A Comparative Exploration of Hybrid Deep Learning and Machine Learning Approach for Advanced Sentiment Analysis Techniques.
Rajesh Das, Kabid Yeiad, Moshfiqur Rahman Ajmain, Jannatul Maowa, Mirajul Islam, Sharun Akter Khushbu · 2023
This paper presents a thorough and extensive investigation into the diverse models and techniques utilized for sentiment analysis.What sets this research apart is the deliberate and purposeful incorporation of data augmentation techniques with the goal of improving the efficacy of sentiment analysis in the Bangla language.We systematically explore various approaches, including preprocessing techniques, advanced models like Long Short-Term Memory (LSTM) and LSTM-CNN (Convolutional Neural Network) Combine, and traditional machine learning models such as Logistic Regression, Decision Tree, Random Forest, Multi-Naive Bayes, Support Vector Machine, and Stochastic Gradient Descent.Our study highlights the substantial impact of data augmentation on enhancing model accuracy and understanding Bangla sentiment nuances.Additionally, we emphasize the LSTM model's ability to capture long-range correlations in Bangla text.Our system scored 0.4129 and ranked 27th among the participants.