Cloud-Based Integrated Real-Time Twitter Grievance Redressal with AWS EC2 and RDS Using Machine Learning Approach for Enhanced Security

Social media platforms, especially Twitter, have become a popular channel for customers to express their grievances related to products or services. Companies need to have an efficient grievance redressal system in place to address these complaints in real-time to ensure customer satisfaction and loyalty. This research paper presents the development of a cloud-based integrated real-time Twitter grievance redressal system using Amazon Web Services (AWS) and machine learning approach. The proposed system uses AWS cloud infrastructure to lever the huge volume of dataset created by tweets and machine learning algorithms to classify and prioritize them based on their severity. The system includes a web application that allows the grievance redressal team to view, categorize, and respond to the tweets efficiently. The efficiency of the planned system is evaluated via a case study. The results show that the system can effectively handle a huge volume of tweets and improve the grievance redressal process. The system’s response time is significantly reduced, and the team can prioritize the tweets based on their severity and importance, leading to better customer satisfaction. Data security is a critical aspect of the proposed real-time application as it will be handling sensitive data of the users. Therefore, security measures such as encryption, MFA, and disaster recovery must be properly implemented and configured, in order to ensure the security of data of the suggested grievance redressal system. The suggested system has achieved an accuracy of 89.5%. This research paper contributes to the development of efficient social media grievance redressal systems using cloud infrastructure and machine learning algorithms. The proposed system can be easily integrated into existing customer relationship management systems, making it a viable solution for companies of all sizes. The system’s ability to handle real-time data and provide quick responses can improve customer trust and loyalty toward the brand, thereby enhancing business growth.