Temporal Analysis of Social Media Response to Live Events: The Milano Fashion Week
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Social media response to catastrophic events, such as natural disasters or terrorist attacks, has received a lot of attention. However, social media are also extremely important in the context of planned events, such as fairs, exhibits, festivals, as they play an essential role in communicating them to fans, interest groups, and the general population. These kinds of events are geo-localized within a city or territory and are scheduled within a public calendar. We consider a specific scenario, the Milano Fashion Week (MFW), which is an important event in our city.
We focus our attention on the spreading of social content in time, measuring the delay of the event propagation. We build different clusters of stakeholders (fashion brands), we characterize several features of time propagation and we correlate it to the popularity of involved actors. We show that the clusters by time and popularity are loosely correlated, and therefore the time response cannot be easily inferred. This motivates the development of a predictor through supervised learning in order to anticipate the space cluster of a new brand.
KeywordsSupport Vector Machine Granger Causality Social Media Platform Live Event Fashion Brand
This work is partly funded by the research project FaST – Fashion Sensing Technology (ID 187010) funded by Regione Lombardia Smart Fashion and Design call. We thank the FashionInProcess group (http://www.fashioninprocess.com) of Politecnico di Milano, and especially Paola Bertola, Chiara Colombi and Federica Vacca, who supported us in the definition of the domain-specific knowledge related to the event.
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