  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.
