Social Media Popularity Prediction (SMPP) is a crucial task that involves automatically predicting future popularity values of online posts, leveraging vast amounts of multimodal data available on social media platforms. Studying and investigating social media popularity becomes central to various online applications and requires novel methods of comprehensive analysis, multimodal comprehension, and accurate prediction. SMP Challenge is an annual research activity that has spurred academic exploration in this area. This paper summarizes the challenging task, data, and research progress. As a critical resource for evaluating and benchmarking predictive models, we have released a large-scale SMPD benchmark encompassing approximately half a million posts authored by around 70K users. The research progress analysis provides an overall analysis of the solutions and trends in recent years. The SMP Challenge website (www.smp-challenge.com) provides the latest information and news.

翻译：社交媒体流行度预测（SMPP）是一项关键任务，旨在利用社交媒体平台上可获取的海量多模态数据，自动预测在线帖子的未来流行度数值。研究并探讨社交媒体流行度已成为各类在线应用的核心，需要综合分析方法、多模态理解及精准预测等新方法。SMP挑战赛是一项年度研究活动，推动了该领域的学术探索。本文总结了该挑战任务、数据及研究进展。作为评估预测模型性能的关键资源，我们发布了大规模SMPD基准数据集，包含约7万用户发布的近50万条帖子。研究进展分析部分对近年来的解决方案和趋势进行了总体分析。SMP挑战赛网站（www.smp-challenge.com）提供最新信息与新闻。