While the scholarship on computer-mediated communication (CMC) can be described as a diverse field of study, with a variety of niche areas and transdisciplinary domains, one of the main recurring research practices within the field involves analytic examinations of digital discourse (Vásquez, 2022). These examinations generally include qualitative and quantitative measures of digital text which is produced, used and re-used in a fast-evolving communicative landscape. Because of the rapid succession of devices, programs and applications that are used for mediation, the methods for analysis sometimes lag behind (as discussed by Herring, 2019). This has raised the question among scholars on how to effectively study and visualise digital discourse, taking into account all affordances and contextual factors that digital resources provide (Car, 2020; Lin, 2015). This paper presents a number of key issues and challenges in the field, bringing together findings from Computer Assisted Language Learning and Learning Analytics studies to provide some new perspectives on CMC text analytics for education.