Several factors can influence the effectiveness of Bayesian filters:
- Word Frequency: Commonly used spam words such as "free," "winner," or "urgent" can increase the likelihood of being flagged. - Email Structure: HTML-heavy emails or those with suspicious attachments are more likely to be considered spam. - Sender Reputation: The sending domain's reputation also plays a significant role. - User Feedback: Filters learn from user behavior, such as marking an email as spam.