Social Media Popularity Prediction
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Social Media Popularity Prediction (SMPP) aims to predict the future popularity (e.g., clicks, views, likes, etc.) of online posts automatically via plenty of social media data from public platforms. It is a crucial problem for social media learning and forecasting and one of the most challenging problems in the field. With the ever-changing user interests and public attention on social media platforms, how to predict popularity accurately becomes more challenging than before. This task is valuable to content providers, marketers, or consumers in a range of real-world applications, including multimedia advertising, recommendation system, or trend analysis.
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SMP Challenge: An Overview and Analysis of Social Media Prediction Challenge
Improving Social Media Popularity Prediction with Multiple Post Dependencies
Ranking news feed updates on social media: A comparative study of supervised models
Sequential Prediction of Social Media Popularity with Deep Temporal Context Networks
Time Matters: Multi-scale Temporalization of Social Media Popularity
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