Understanding Brand Authenticity Sentiments using Big Data Analytics

Abstract

Social media is the major place where people share their feelings in reviews and opinions about anything such as events, products, people, article and many more. These sentiments have great influence on readers who read those opinions and construct their own opinions in the matters. The unstructured data collected from varied sources needs to be analyzed and well-structured to address specific market questions and for this purpose sentiment analysis has received considerable attention over the years. Sentiment analysis is used to decipher the mind-set or feelings of a writer from his review. Many scholars have discussed the ability of deep learning models to resolve the question of knowing consumer emotions. In this paper, we are interested in handling the sentiment analysis task using various deep learning models such as Simple Neural Network, Convolutional Neural Network (CNN) and two Recurrent Neural Networks (RNN) -Long Short Term Memory (LSTM) and Gated Recurrent Unit (GRU).