Identification of bots on Twitter can be difficult, and successful approaches often use an iterative workflow, applying different techniques to identify discrete groups of bots. This paper presents first results of the application of this iterative workflow to the Australian TrISMA collection, which contains the tweets of over 4 million Twitter accounts identified as being Australian. To our knowledge, this research undertakes the first comprehensive identification of bots in the Australian Twittersphere. The identified bots are then classified by bot type before the proportion of overall account and tweet numbers they represent is determined.