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TikTok is a popular new social media, where users express themselves throughshort video clips. A common form of interaction on the platform isparticipating in "challenges", which are songs and dances for users to iterateupon. Challenge contagion can be measured through replication reach, i.e.,users uploading videos of their participation in the challenges. The uniquenessof the TikTok platform where both challenge content and user preferences areevolving requires the combination of challenge and user representation. Thispaper investigates social contagion of TikTok challenges through predicting auser's participation. We propose a novel deep learning model, deepChallenger,to learn and combine latent user and challenge representations from past videosto perform this user-challenge prediction task. We collect a dataset of over7,000 videos from 12 trending challenges on the ForYouPage, the app's landingpage, and over 10,000 videos from 1303 users. Extensive experiments areconducted and the results show that our proposed deepChallenger (F1=0.494)outperforms baselines (F1=0.188) in the prediction task.

Will You Dance To The Challenge? Predicting User Participation of TikTok Challenges