A Model for Detecting Events from Twitter Data with Rough Accuracy
K. Vasumathi, S. Selvakani, J. Vellaiyan · International Journal of Darshan Institute on Engineering Research and Emerging Technologies · 2023
The usage of mobile devices is growing every day, leading to a significant surge in SMS traffic.SMS, a text messaging service available on both regular and smartphones, has also resulted in an increase in spam texts.Spammers aim to send unsolicited messages to gain financial or commercial benefits, such as credit card details, market growth, lottery tickets, and more.Consequently, spam detection has become a priority, and our work focuses on detecting SMS spam using a combination of machine learning and deep learning techniques.To build our spam detection model, we utilized data from UCI, achieving an accuracy rate of 98.5%, which surpasses previous models.Our implementation was completed using Python.