SMP Challenge - Social Media Prediction Challenge 2026

Bo Wu, Peiye Liu, Jia Wang, Zhaoyang Zeng, Qiushi Huang, Bei Liu, Jiebo Luo, Wen-Huang Cheng

Keywords: Social Multimedia, Multimodal Learning, User Behavior, Computer Vision, Language Modeling

Abstract: SMP Challenge is an annual challenge that seeks excellent research teams on new ways of forecasting problems and meaningfully improving people’s social lives and business scenarios. The enormous amounts of online content lead to overconsumption, online word-of-mouth helps us to efficiently discover interesting news, emerging topics, the latest stories, or amazing products from the information ocean. Therefore, predicting online popularity became an emerging and significant task for online media, brand marketing, social influencers, or our individuals. The challenge Social Media Popularity Prediction (SMPP) aims at predicting the impact of online post sharing on large-scale social multimedia benchmarks. It is central to various scenarios, such as online advertising, social recommendation, demand forecasting, etc.

Email Sharing: We authorize the sharing of all author emails with Program Chairs.

Data Release: We authorize the release of our submission and author names to the public in the event of acceptance.

Submission Number: 13