An Intelligent Framework Based on Deep Learning for SMS and e‐mail Spam Detection
The use of short message service (SMS) and e‐mail have increased too much over the last
decades. 80% of people do not read e‐mails while 98% of cell phone users daily read their …
decades. 80% of people do not read e‐mails while 98% of cell phone users daily read their …
Forecasting the S&P 500 index using mathematical-based sentiment analysis and deep learning models: a FinBERT transformer model and LSTM
Stock price prediction has been a subject of significant interest in the financial mathematics
field. Recently, interest in natural language processing models has increased, and among …
field. Recently, interest in natural language processing models has increased, and among …
Extending limited datasets with GAN-like self-supervision for SMS spam detection
Abstract Short Message Service (SMS) spamming is a harmful phishing attack on mobile
phones. That is, fraudsters are trying to misuse personal user information, using tricky text …
phones. That is, fraudsters are trying to misuse personal user information, using tricky text …
A comprehensive analysis of forecasting elections using social media text
Modern social media's rise to prominence has altered the ways in which candidates reach
out to voters and conduct campaigns. Researchers often dwell upon the uses of social …
out to voters and conduct campaigns. Researchers often dwell upon the uses of social …
[HTML][HTML] Oecnet: Optimal feature selection-based email classification network using unsupervised learning with deep cnn model
SR Borra, M Yukthika, M Bhargavi, M Samskruthi… - e-Prime-Advances in …, 2024 - Elsevier
The escalating prevalence of email communication in global interactions underscores the
critical need for robust security measures. However, the existing methods to safeguard email …
critical need for robust security measures. However, the existing methods to safeguard email …
[HTML][HTML] An integrated approach to Bayesian weight regulations and multitasking learning methods for generating emotion-based content in the metaverse
This paper introduces an integrated model designed to analyze topics and sentiments in
textual data simultaneously, recognizing their interdependence. By tackling challenges such …
textual data simultaneously, recognizing their interdependence. By tackling challenges such …
[PDF][PDF] SMS Spam Detection System Based on Deep Learning Architectures for Turkish and English Messages
Short Message Service (SMS) still continues its existence despite the emergence of different
messaging services. It plays a part in our lives as a communication service. Companies use …
messaging services. It plays a part in our lives as a communication service. Companies use …
Guide for the application of the data augmentation approach on sets of texts in Spanish for sentiment and emotion analysis
Over the last ten years, social media has become a crucial data source for businesses and
researchers, providing a space where people can express their opinions and emotions. To …
researchers, providing a space where people can express their opinions and emotions. To …
Complex-network based model for SMS spam filtering
With the advancement of technology and the widespread use of mobile phones and wireless
communication, SMS has become the most popular texting method due to its high response …
communication, SMS has become the most popular texting method due to its high response …
CatRevenge: towards effective revenge text detection in online social media with paragraph embedding and CATBoost
Huge amount of internet data are produced and consumed by internet users, where most of
the data are in natural language and they express their feelings, emotions and thoughts on …
the data are in natural language and they express their feelings, emotions and thoughts on …