Premium
Senti‐eSystem : A sentiment‐based eSystem ‐using hybridized fuzzy and deep neural network for measuring customer satisfaction
Author(s) -
Asghar Muhammad Zubair,
Subhan Fazli,
Ahmad Hussain,
Khan Wazir Zada,
Hakak Saqib,
Gadekallu Thippa Reddy,
Alazab Mamoun
Publication year - 2021
Publication title -
software: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 70
eISSN - 1097-024X
pISSN - 0038-0644
DOI - 10.1002/spe.2853
Subject(s) - customer satisfaction , computer science , artificial neural network , fuzzy logic , lexicon , artificial intelligence , polarity (international relations) , sentiment analysis , data mining , business , marketing , chemistry , biochemistry , cell
Summary In the competing era of online industries, understanding customer feedback and satisfaction is one of the important concern for any business organization. The well‐known social media platforms like Twitter are a place where customers share their feedbacks. Analyzing customer feedback is beneficial, as it provides an advantage way of unveiling customer interests. The proposed system, namely Senti‐eSystem , aims at the development of sentiment‐based eSystem using hybridized Fuzzy and Deep Neural Network for Measuring Customer Satisfaction to assist business organizations for improving the quality of their services and products. The proposed approach initially deploys a Bidirectional Long Short Term Memory with attention mechanism to predict the sentiment polarity that is positive and negative, followed by Fuzzy logic approach to determine the customer satisfaction level, which further strengthens the capabilities of the proposed approach. The system achieves an accuracy of 92.86%, outperforming the previous state‐of‐art lexicon‐based approaches. Moreover, the effectiveness of the proposed system is also validated by applying the statistical test.