Emotion Detection Using Bi-directional LSTM with an Effective Text Pre-processing Method
Sumanathilaka TGDK, Viggnah Selvarai, Uddav Raj, Venkatesh P Raiu, Jay Prakash · 2021
In a real-life scenario, extracting emotion from unstructured text is an active and challenging area of research. It has diverse applications in various aspects of our daily life To overcome various challenges involved in detecting emotion from text, researchers from diverse fields applied various machine learning algorithms. However, deep learning methods such as long short-term memory is effective to detect emotion by maintaining the sequence structure of the text. In this work, we use Bi-directional long short-term memory with attention layer for emotion detection for better accuracy for prediction. In addition, we employ a text preprocessing method to improve further results. We perform the experiments on three data sets and the models are evaluated based on the classification accuracy.