research-article

On popularity prediction of videos shared in online social networks

Authors:

Jiangchuan Liu,

Ke XuAuthors Info & Claims

CIKM '13: Proceedings of the 22nd ACM international conference on Information & Knowledge Management

Pages 169 - 178

https://doi.org/10.1145/2505515.2505523

Published: 27 October 2013 Publication History

Abstract

Popularity prediction, with both technological and economic importance, has been extensively studied for conventional video sharing sites (VSSes), where the videos are mainly found via searching, browsing, or related links. Recent statistics however suggest that online social network (OSN) users regularly share video contents from VSSes, which has contributed to a significant portion of the accesses; yet the popularity prediction in this new context remains largely unexplored. In this paper, we present an initial study on the popularity prediction of videos propagated in OSNs along friendship links.

We conduct a large-scale measurement and analysis of viewing patterns of videos shared in one of largest OSNs in China, and examine the performance of typical views-based prediction models. We find that they are generally ineffective, if not totally fail, especially when predicting the early peaks and later bursts of accesses, which are common during video propagations in OSNs. To overcome these limits, we track the propagation process of videos shared in a Facebook-like OSN in China, and analyze the user viewing and sharing behaviors. We accordingly develop a novel propagation-based video popularity prediction solution, namely SoVP. Instead of relying solely on the early views for prediction, SoVP considers both the intrinsic attractiveness of a video and the influence from the underlying propagation structure. The effectiveness of SoVP, particularly for predicting the peaks and bursts, have been validated through our trace-driven experiments.

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Cited By

Lin HZhang Z(2024)Modeling the Social Influence Effectiveness of Popular Weibo EventsComplexity10.1155/2024/64571152024Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1155/2024/6457115
Zhong TLang JZhang YCheng ZZhang KZhou FHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)Predicting Micro-video Popularity via Multi-modal Retrieval AugmentationProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657929(2579-2583)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3657929
Liu XMiao CFiumara GDe Meo P(2024)Information Propagation Prediction Based on Spatial–Temporal Attention and Heterogeneous Graph Convolutional NetworksIEEE Transactions on Computational Social Systems10.1109/TCSS.2023.324457311:1(945-958)Online publication date: Feb-2024
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Index Terms

On popularity prediction of videos shared in online social networks
1. Applied computing
  1. Law, social and behavioral sciences
2. Information systems
  1. World Wide Web
    1. Web applications
    2. Web services

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cover image ACM Conferences

CIKM '13: Proceedings of the 22nd ACM international conference on Information & Knowledge Management

October 2013

2612 pages

ISBN:9781450322638

DOI:10.1145/2505515

General Chairs:
Qi He
LinkedIn, USA
,
Arun Iyengar
IBM T.J. Watson Research Center, USA
,
Program Chairs:
Wolfgang Nejdl
L3S Research Center, Germany
,
Jian Pei
Simon Fraser University, Canada
,
Rajeev Rastogi
Amazon, India

Copyright © 2013 ACM.

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Published: 27 October 2013

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October 27 - November 1, 2013

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Cited By

Lin HZhang Z(2024)Modeling the Social Influence Effectiveness of Popular Weibo EventsComplexity10.1155/2024/64571152024Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1155/2024/6457115
Zhong TLang JZhang YCheng ZZhang KZhou FHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)Predicting Micro-video Popularity via Multi-modal Retrieval AugmentationProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657929(2579-2583)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3657929
Liu XMiao CFiumara GDe Meo P(2024)Information Propagation Prediction Based on Spatial–Temporal Attention and Heterogeneous Graph Convolutional NetworksIEEE Transactions on Computational Social Systems10.1109/TCSS.2023.324457311:1(945-958)Online publication date: Feb-2024
https://doi.org/10.1109/TCSS.2023.3244573
Yingying CWenhui HXueyang LHaoxuan WXiankui ZJiaxi W(2024)User Dual Intents Graph Modeling for Information Diffusion Prediction2024 IEEE 10th Conference on Big Data Security on Cloud (BigDataSecurity)10.1109/BigDataSecurity62737.2024.00014(35-40)Online publication date: 10-May-2024
https://doi.org/10.1109/BigDataSecurity62737.2024.00014
Jin YLee YSharma KYe MSikka KDivakaran AKumar SSingh ASun YAkoglu LGunopulos DYan XKumar ROzcan FYe J(2023)Predicting Information Pathways Across Online CommunitiesProceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3580305.3599470(1044-1056)Online publication date: 4-Aug-2023
https://doi.org/10.1145/3580305.3599470
Yang YLou KWang ELiu WShang JSong XLi DWu J(2023)Multi-Agent Reinforcement Learning Based File Caching Strategy in Mobile Edge ComputingIEEE/ACM Transactions on Networking10.1109/TNET.2023.327803231:6(3159-3174)Online publication date: 1-Jun-2023
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Xie JZhu YChen Z(2023)Micro-Video Popularity Prediction Via Multimodal Variational Information BottleneckIEEE Transactions on Multimedia10.1109/TMM.2021.312053725(24-37)Online publication date: 2023
https://doi.org/10.1109/TMM.2021.3120537
Zhang HHuang SWang XLi JWang XLeung V(2023)A Measurement-Driven Analysis and Prediction of Content Propagation in the Device-to-Device Social NetworksIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2022.321939935:8(7651-7664)Online publication date: 1-Aug-2023
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Zhang ZXu SGuo LLian W(2022)Multi-modal Variational Auto-Encoder Model for Micro-video Popularity PredictionProceedings of the 8th International Conference on Communication and Information Processing10.1145/3571662.3571664(9-16)Online publication date: 3-Nov-2022
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Chen XZhou XChan JChen LSellis TZhang Y(2022)Event Popularity Prediction Using Influential Hashtags From Social MediaIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2020.304842834:10(4797-4811)Online publication date: 1-Oct-2022
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