The paper reports findings from a FAIR principles-based research project dedicated to investigating how cross-field research between the DH and Sociotechnical Sustainable Transport Research could help to enhance the holistic understanding of sociotechnical low-carbon transport transitions.  Using the hashtag search queries #sustainabletransport and #sustainablemobility, 33,121 Tweets (2013-2021) and 8,089 Instagram images including captions (2017/2018-2021) were mined using Python scripts. Quantitative text and sentiment analyses were applied to the Tweets and image captions. Additionally, an automated image analysis using the Instagram dataset was conducted. Synthesized results formed the base for the cross-platform analysis comprising: 1) hot topics, 2) mentioned users, 3) sentiment, 4) co-hashtags. Data were visualized via Tableau, Excel, RAWGraphs, and Bubbl.us. Whereas electromobility, one of Holden et al.’s Grand Narratives for sustainable mobility, has been significantly present in the digital discourse on both platforms (especially Instagram), #sustainabletransport has been closely associated with active transport, especially bicycling, and #sustainablemobility with the electromobility theme. The study has demonstrated the investigative potentials of cross-field cross-platform social media analysis studies and ultimately DH to enhance the understanding of sociotechnical low-carbon transport transitions. Drawing on core results, the paper also suggests an adapted version of the Geelsean Multi-Level Perspective.