Spam Content Filtering in Online Social Networks
Meenakshi Meenakshi · 2025
In the contemporary period, individuals engage in both professional and personal contacts mostly through electronic modes of communication. Over the past decade, the popularity and influence of email and social media platforms such as LinkedIn, Facebook, and Twitter have experienced a significant and rapid increase. Online social networking platforms and email are exploited by spammers to distribute their messages, taking advantage of their popularity. The spam filtering system must possess sufficient robustness to effectively detect and prevent unwanted communications, hence halting spammers’ activities promptly. When attempting to recognize spam communications, the majority of individuals rely on either text-based or collaborative methods. To improve the accuracy of spam detection in emails and social networks, it is necessary to employ strategies that reduce the occurrence of false positives and false negatives. Support vector machines are the most effective method for categorizing and detecting spam emails.