The rise of social media has changed the nature of the fashion industry. Influence is no longer concentrated in the hands of an elite few: social networks have distributed power across a broader set of tastemakers. To understand this new landscape of influence, we created FITNet --- a network of 10,000 fashion-related Twitter accounts that heavily influence the larger Twitter fashion graph. To construct FITNet, we trained a content-based classifier to predict which accounts are related to fashion. Leveraging this classifier, we estimated the size of Twitter's fashion subgraph, snowball sampled more than 300k fashion-related accounts based on following relationships, and identified the top 10,000 influencers, or FITNet, in the resulting subgraph. We asked 55 fashion undergraduates to validate and further categorize the accounts in FITNet. These categorizations allow us to analyze interactions between influential people, brands, retailers, and media in fashion.
https://doi.org/10.1145/3449227
The 24th ACM Conference on Computer-Supported Cooperative Work and Social Computing