Spam Detection using Word Embedding-based LSTM
Supphawarich Thanarattananakin, Suwanna Bulao, Busarin Visitsilp, Maleerat Maliyaem · 2022 Joint International Conference on Digital Arts, Media and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering (ECTI DAMT & NCON) · 2022
Spam email is a well-known problem in network communications. A large number of spam emails in mailbox caused inconvenience and might lead to cybercrime. Effective spam mail detection is one of challenges research topics. This paper proposed a new spam mail detection approach that can be applied for sentiment analysis. A dataset of 5,572 messages was tested using Word embedding Techniques such as Bag of words, Hashing, and Long short-term memory network Algorithm (LSTM). The results showed the proposed method performance are equal 98%, 93%, 95%, and 98% interns of precision, recall, F1-score, and accuracy respectively.