  Topics play an important role in the global organisation of a conversation as
what is currently discussed constrains the possible contributions of the
participant. Understanding the way topics are organised in interaction would
provide insight on the structure of dialogue beyond the sequence of utterances.
However, studying this high-level structure is a complex task that we try to
approach by first segmenting dialogues into smaller topically coherent sets of
utterances. Understanding the interactions between these segments would then
enable us to propose a model of topic organisation at a dialogue level. In this
paper we work with open-domain conversations and try to reach a comparable
level of accuracy as recent machine learning based topic segmentation models
but with a formal approach. The features we identify as meaningful for this
task help us understand better the topical structure of a conversation.
