A recent reading on research methodology that has turned out to be rather impactful to me is Norris’s new book, Systematically Working With Multimodal Data: Research Methods in Multimodal Discourse Analysis, published just 2019. For a good while now, I’ve been trying to find a toolkit for making sense of how meanings are communicated on videos – a systematic toolkit that would help me deal with the overwhelming material that one video can contain. While first reading it, I had somewhat mixed feelings about multimodal discourse analysis (MDA). On one hand, it was intimidating to read about the level of detail in transcription that noted someone’s hand going up and down three times when they scratched their nose – that is, I’m not sure whether the level of detail that MDA goes into in transcribing lower-level mediated actions (‘a mode’s smallest pragmatic meaning unit’) is what I’m looking for in my research. On the other hand, now that I know of such a systematic and detailed way of transcribing and noting actions in videos, it seems impossible not to want to use it for absolutely everything (although perhaps combined with some other approach). And it does help that MDA guides you to focus on multimodally transcribing only the parts that are relevant to answering your research question, since it would take too much time and might even be counter productive to transcribe the whole video. The book specifically warns you not to start immediately transcribing (especially speech because this puts the focus on spoken language), but to first to take notes, get an overall understanding of the present higher-level mediated actions (for example, Skyping is one), and then decide which parts are relevant for a detailed micro analysis.
The step-by-step guidelines offered by the book are clear and helpful, but also a bit overwhelming initially, since when the process is broken down to pieces, it seems there are endless steps to the analysis. Once one actually starts doing it, it may not turn out to be that bad, especially after some experience and having figured out, for example, which programs to use for transcription.
I’m almost certain that I’ll end up making use of MDA as suggested by Norris sooner or later; I’ve included it as part of the methodology in my recent chapter proposals and funding applications because although MDA alone doesn’t seem enough to answer the questions I aim to answer, it seems such a valuable tool for working with video data.