Email (or electronic mail) is a popular communication method used in both internal and internet networks for information exchange. While email has significant benefits, its misuse can have negative impacts if not used wisely. Spam (meaning Stupid Pointless Annoying Messages) comes in various types, including advertisements, phishing, malware viruses, scams, and others. Spam is the pervasive nature of unsolicited and often malicious messages. The impact of spam extends beyond annoyance, as it poses risks to personal information security and hampers productivity. In its various insidious forms, spam continues to plague digital communication channels, ranging from email inboxes to social media platforms. Spam detection has evolved significantly from rudimentary rule-based systems to sophisticated approaches leveraging natural language processing (NLP) and machine learning. NLP has become the cornerstone of modern defense systems because NLP approach provides better performance in spam detection compared to other methods. This paper explores the pivotal role of NLP in spam detection.
natural language processing (NLP), computational linguistics, spam detection, emails, artificial intelligence, machine learning.
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