Predicting style breaches within textual content

Method for facilitating predicting style breaches within content. The method involves obtaining target content comprising content created by a plurality of individuals, identifying style features associated with a plurality of content segments within the target content and then using the style features and a style breach prediction model to predict style breaches within the content. The style breaches indicating a change the writing style of text within the target content. The style features may comprise lexical features and/or syntactic features. The lexical features may comprise one or more of an average word length, a sentence length, a word length frequency, a Flesh-Kincaid readability score, a frequency of words not in the English dictionary, a Honore's Index value, a Hapax legomena value, a Hapax dislegomena value, a Yule's Index value and a token ratio. Also disclosed is a method for facilitating a style breach prediction model by collecting training content, identifying style features in the training content, obtaining style breach annotations associated with the training content, the annotations indicating positions at which style within the training content is perceived as different and training a style breach prediction model to predict changes in text style within content using this method.