Identifying Interpersonal Distance Using Systemic Features

This chapter uses Systemic Functional Linguistic (SFL) theory as a basis for extracting semantic features of documents. We focus on the pronominal and determination system and the role it plays in constructing interpersonal distance. By using a hierarchical system model that represents the author's language choices, it is possible to construct a richer and more informative feature representation with superior computational efficiency than the usual bag-of-words approach. Experiments within the context of financial scam classification show that these systemic features can create clear separation between registers with different interpersonal distance. This approach is generalizable to other aspects of attitude and affect that have been modelled within the systemic functional linguistic theory.