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Understanding Video Sharing Propagation in Social Networks: Measurement and Analysis

Published: 04 July 2014 Publication History

Abstract

Modern online social networking has drastically changed the information distribution landscape. Recently, video has become one of the most important types of objects spreading among social networking service users. The sheer and ever-increasing data volume, the broader coverage, and the longer access durations of video objects, however, present significantly more challenges than other types of objects. This article takes an initial step toward understanding the unique characteristics of video sharing propagation in social networks. Based on realworld data traces from a large-scale online social network, we examine the user behavior from diverse aspects and identify different types of users involved in video propagation. We closely investigate the temporal distribution during propagation as well as the typical propagation structures, revealing more details beyond stationary coverage. We further extend the conventional epidemic models to accommodate diverse types of users and their probabilistic viewing and sharing behaviors. The model, effectively capturing the essentials of the propagation process, serves as a valuable basis for such applications as workload synthesis, traffic prediction, and resource provision of video servers.

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      Published In

      cover image ACM Transactions on Multimedia Computing, Communications, and Applications
      ACM Transactions on Multimedia Computing, Communications, and Applications  Volume 10, Issue 4
      June 2014
      132 pages
      ISSN:1551-6857
      EISSN:1551-6865
      DOI:10.1145/2656131
      Issue’s Table of Contents
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 04 July 2014
      Accepted: 01 February 2014
      Revised: 01 January 2014
      Received: 01 March 2013
      Published in TOMM Volume 10, Issue 4

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      Author Tags

      1. Social network
      2. information propagation
      3. measurement
      4. video sharing

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      Cited By

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      • (2022)Using Heterogeneous Cloud Computing to Manage Resources in Sustainable Cyber-Physical Systems2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)10.1109/SMART55829.2022.10047642(153-157)Online publication date: 16-Dec-2022
      • (2018)Resource Management in Sustainable Cyber-Physical Systems Using Heterogeneous Cloud ComputingIEEE Transactions on Sustainable Computing10.1109/TSUSC.2017.27239543:2(60-72)Online publication date: 1-Apr-2018
      • (2017)Path-Based Epidemic Spreading in NetworksIEEE/ACM Transactions on Networking10.1109/TNET.2016.259438225:1(565-578)Online publication date: 1-Feb-2017
      • (2017)The future of online social networks (OSN)Telematics and Informatics10.1016/j.tele.2016.10.00934:5(498-517)Online publication date: 1-Aug-2017
      • (2016)Workload CharacterizationACM Computing Surveys10.1145/285612748:3(1-43)Online publication date: 8-Feb-2016
      • (2016)Migration towards cloud-assisted live media streamingIEEE/ACM Transactions on Networking10.1109/TNET.2014.236254124:1(272-282)Online publication date: 1-Feb-2016
      • (2016)Modeling Interest-Driven Data Dissemination in Online Social Networks2016 12th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN)10.1109/MSN.2016.053(290-295)Online publication date: Dec-2016
      • (2016)Social-aware video delivery: challenges, approaches, and directionsIEEE Network10.1109/MNET.2016.757902430:5(35-39)Online publication date: Sep-2016
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