mlsanityData to 14 Oct 2026

SMP Challenge: An Overview and Analysis of Social Media Prediction Challenge

arXiv 2405.10497 ↗First posted 17 May 2024cs.MM cs.AI cs.CVcited by 4

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Abstract (arXiv)

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.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 9 of its 35 references that are in the map. First posted on arXiv 17 May 2024.

Builds on

9 of 35 references.

References · 9

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2016XGBoost: A Scalable Tree Boosting Systemcited by 5,166
  3. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,375
  4. 2016Aggregated Residual Transformations for Deep Neural Networkscited by 2,546
  5. 2016TiDeH: Time-Dependent Hawkes Process for Predicting Retweet Dynamicscited by 15
  6. 2017Sequential Prediction of Social Media Popularity with Deep Temporal Context Networkscited by 12
  7. 2016Predictability of Popularity: Gaps between Prediction and Understandingcited by 7
  8. 2019SMP Challenge: An Overview of Social Media Prediction Challenge 2019cited by 5
  9. 2014The Bursty Dynamics of the Twitter Information Networkcited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 2.

4 papers.

  1. 2025MVP: Winning Solution to SMP Challenge 2025 Video Trackcited by 14
  2. 2026OmniTrend: Content-Context Modeling for Scalable Social Popularity Predictioncited by 1
  3. 2025HyperFusion: Hierarchical Multimodal Ensemble Learning for Social Media Popularity Predictioncited by 0
  4. 2026Benchmarking Multi-Modal Graph-based Social Media Popularity Predictioncited by 0