Álvaro Luna-García’s scientific contributions

The purpose of this research is to understand how the most sustainable fashion brands, according to five corporate sustainability rankings, use Instagram to disseminate messages related to the field of sustainability, as well as how such communications are received by their followers, not only in terms of engagement but also by analyzing the favourability sentiment of their comments. The research was conducted through a quantitative content analysis, using automated semantic analysis tools of Instagram posts by sustainable fashion brands. This analysis generated a dataset with 277,955 published posts, which was filtered, only including publications that contained specific words related to sustainability, resulting in the final analysis of 12,639 publications. This study contributes to understanding how sustainable fashion brands effectively communicate sustainability-related topics and news on social networks like Instagram, which helps spark interest and generate a positive dialogue with their audience. Findings indicate that this type of content can be useful for generating a positive conversation with their social media followers, as well as the importance of analyzing the sentiment of such interactions when considering the communicative effectiveness of posts. The use of automated semantic analysis tools allowed for a more representative sample of sustainable fashion brands to be covered, providing data-based evidence of the different factors that can influence engagement and favourability of sustainable communication in fashion.