mlsanityData to 7 Oct 2026

Enhancing Social Media Post Popularity Prediction with Visual Content

arXiv 2405.02367 ↗First posted 3 May 2024cs.LG cs.CVcited by 0

Not on the map. Why?

Abstract (arXiv)

Our study presents a framework for predicting image-based social media content popularity that focuses on addressing complex image information and a hierarchical data structure. We utilize the Google Cloud Vision API to effectively extract key image and color information from users' postings, achieving 6.8% higher accuracy compared to using non-image covariates alone. For prediction, we explore a wide range of prediction models, including Linear Mixed Model, Support Vector Regression, Multi-layer Perceptron, Random Forest, and XGBoost, with linear regression as the benchmark. Our comparative study demonstrates that models that are capable of capturing the underlying nonlinear interactions between covariates outperform other methods.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 12 of its 79 references that are in the map. First posted on arXiv 3 May 2024.

Builds on

12 of 79 references.

References · 12

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2017A Unified Approach to Interpreting Model Predictionscited by 6,488
  3. 2016XGBoost: A Scalable Tree Boosting Systemcited by 5,120
  4. 2022BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generationcited by 4,310
  5. 2013A Bayesian approach for predicting the popularity of tweetscited by 12
  6. 2020Predicting the Popularity of Micro-videos with Multimodal Variational Encoder-Decoder Frameworkcited by 8
  7. 2015Understanding Image Viralitycited by 7
  8. 2015Predicting popularity of online videos using Support Vector Regressioncited by 7
  9. 2016Predictability of Popularity: Gaps between Prediction and Understandingcited by 7
  10. 2021Multimodal Deep Learning Framework for Image Popularity Prediction on Social Mediacited by 6
  11. 2018How to Become Instagram Famous: Post Popularity Prediction with Dual-Attentioncited by 5
  12. 2017Cats and Captions vs. Creators and the Clock: Comparing Multimodal Content to Context in Predicting Relative Popularitycited by 4

Built on by

Not cited yet.