Content-based mobile spam classification using stylistically motivated features

The feature of brevity in mobile phone messages makes it difficult to distinguish lexical patterns to identify spam. This paper proposes a novel approach to spam classification of extremely short messages using not only lexical features that reflect the content of a message but new stylistic features that indicate the manner in which the message is written. Experiments on two mobile phone message collections in two different languages show that the approach outperforms previous content-based approaches significantly, regardless of language.