Methodological considerations in corpus-based digital genre research: The case of the online music review

The growing number of digital genres has led to an increase in the number of studies in the realm of genre analysis. The primary aim of these studies is to demystify the structure of digital genres by annotating the smallest communicative units (steps) that can be grouped into macrounits (moves) (Moreno & Swales, 2018; Kessler & Polio, 2023). The aim of this paper is to address the methodological challenges that could help better systematise and structure research into digital genres. The case in point is the genre analysis of 102 online music reviews drawn from 3 salient websites (Pitchfork, Slant Magazine and NME). The paper addresses the issues of corpus design, i.e., the choice of variables (time, music genre, review rating) as well as corpus representativity and collection. The paper also sheds light on the importance of annotation consistency and transparent codebook labels that are crucial to ensure reproducibility of results. The issues of methodological transparency and rigour that should precede annotation are discussed, i.e., calculating interrater agreement and pilot testing (Kim et al., 2024). Furthermore, it is also shown that accounting for non-textual semiotic resources such as album covers, images and music videos is vital to create a credible portrayal of the digital music review genre with all of its technological affordances. The findings illustrate that methodological rigour facilitates drawing firm conclusions when comparing one’s results with similar studies.