SMP Challenge: An Overview of Social Media Prediction Challenge 2019
October 04, 2019 ยท Declared Dead ยท ๐ ACM Multimedia
"No code URL or promise found in abstract"
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Authors
Bo Wu, Wen-Huang Cheng, Peiye Liu, Bei Liu, Zhaoyang Zeng, Jiebo Luo
arXiv ID
1910.01795
Category
cs.MM: Multimedia
Cross-listed
cs.LG,
cs.SI
Citations
45
Venue
ACM Multimedia
Last Checked
2 months ago
Abstract
"SMP Challenge" aims to discover novel prediction tasks for numerous data on social multimedia and seek excellent research teams. Making predictions via social multimedia data (e.g. photos, videos or news) is not only helps us to make better strategic decisions for the future, but also explores advanced predictive learning and analytic methods on various problems and scenarios, such as multimedia recommendation, advertising system, fashion analysis etc. In the SMP Challenge at ACM Multimedia 2019, we introduce a novel prediction task Temporal Popularity Prediction, which focuses on predicting future interaction or attractiveness (in terms of clicks, views or likes etc.) of new online posts in social media feeds before uploading. We also collected and released a large-scale SMPD benchmark with over 480K posts from 69K users. In this paper, we define the challenge problem, give an overview of the dataset, present statistics of rich information for data and annotation and design the accuracy and correlation evaluation metrics for temporal popularity prediction to the challenge.
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