How to Engage Followers: Classifying Fashion Brands According to Their Instagram Profiles, Posts and Comments


Stefanie Scholz1 and Christian Winkler2, 1Wilhem Loehe University of Applied Sciences, Germany, 2datanizing GmbH, chwarzenbruck, Germany


In this article we show how fashion brands communicate with their follower on Instagram. We use a continuously update dataset of 68 brands, more than 300,000 posts and more than 40,000,000 comments.Starting with descriptive statistics, we uncover different behavior and success of the various brands. It turns out that there are patterns specific to luxury, mass-market and sportswear brands. Posting volume is extremely brand dependent as is the number of comments and the engagement of the community.Having understood the statistics, we turn to machine learning techniques to measure the response of the community via comments. Topic models help us understand the structure of their respective community and uncover insights regarding the response to campaigns. Having up-to-date content is essential for this kind of analysis, as the market is highly volatile.Furthermore, automatic data analysis is crucial to measure the success of campaigns and adjust them accordingly for maximum effect.


Instagram, Fashion Brands, Data Extraction, Marketing, Analysis, Artificial Intelligence, Netnography, Descriptive Statistics, Visualization, Community Engagement, Artificial Intelligence, Unsupervised Learning, Topic Modelling.

Full Text  Volume 10, Number 17