Data Science in R

Chapter 3

Using Statistics to Identify Spam

Deborah Nolan

University of California, Berkeley

Duncan Temple Lang

University of California, Davis

3.1 Introduction

People are terrific at spotting spam in their mail reader with a quick glance at the subject line and sender, and when that approach is not conclusive, a glimpse at the contents of the message is usually enough to classify the message. But how do we design an automated procedure to classify and eliminate these unwanted messages to save us the time and irritation of having to sort through them in our inbox? Spam filters used by mail readers examine various characteristics of an email before deciding whether to place it in your inbox or spam folder. This decision is in part based on a statistical ...