Henrique Pinto
ABSTRACT
Predicting Web content popularity is an important task for supporting the design and evaluation of a wide range of systems, from targeted advertising to effective search and recommendation services. We here present two simple models for predicting the future popularity of Web content based on historical information given by early popularity measures. Our approach is validated on datasets consisting of videos from the widely used YouTube video-sharing portal. Our experimental results show that, compared to a state-of-the-art baseline model, our proposed models lead to significant decreases in relative squared errors, reaching up to 20% reduction on average, and larger reductions (of up to 71%) for videos that experience a high peak in popularity in their early days followed by a sharp decrease in popularity.
- Alexa.com. Alexa top 500 global sites. http://www.alexa.com/topsites, 2011. {Online; acessed 2-November-2011}.Google Scholar
- S. Boyd and L. Vandenberghe. Convex optimization. Cambridge University Press, 2004. Google ScholarCross Ref
- M. Cha, H. Kwak, P. Rodriguez, Y. Ahn, and S. Moon. Analyzing the video popularity characteristics of large-scale user generated content systems. ACM Trans. on Networking, 17(5), 2009. Google ScholarDigital Library
- M. Cha, H. Kwak, P. Rodriguez, Y.-Y. Ahn, and S. Moon. I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system. In Proc. ACM Internet Measurement Conference, 2007. Google ScholarDigital Library
- R. Crane and D. Sornette. Robust dynamic classes revealed by measuring the response function of a social system. Proc. National Academy of Sciences, 105(41), 2008.Google Scholar
- F. Figueiredo, F. Benevenuto, and J. Almeida. The tube over time: Characterizing popularity growth of youtube videos. In Proc. Conference of Web Search and Data Mining , 2011. Google ScholarDigital Library
- J. Friedman, T. Hastie, and R. Tibshirani. The elements of statistical learning, volume 1. Springer Series in Statistics, 2001.Google Scholar
- M. Gonçalves, J. Almeida, L. Santos, A. Laender, and V. Almeida. On popularity in the blogosphere. Internet Computing, 14(3), 2010. Google ScholarDigital Library
- V. Heffernan. Uploading the avant-garde. http://www.nytimes.com/2009/09/06/magazine/06FOB-medium-t.html, 2009. {Online; acessed 2-November-2011}.Google Scholar
- R. Jain. The art of computer systems performance analysis. John Wiley & Sons, 2008.Google Scholar
- J. Lee, S. Moon, and K. Salamatian. An approach to model and predict the popularity of online contents with explanatory factors. In Int'l. Conf. on Web Intelligence and Intelligent Agent Technology, 2010. Google ScholarDigital Library
- K. Lerman and T. Hogg. Using a model of social dynamics to predict popularity of news. In Proc. World Wide Web Conference. ACM, 2010. Google ScholarDigital Library
- T. Rodrigues, F. Benevenuto, V. Almeida, J. Almeida, and M. Gonçalves. Equal but different: A contextual analysis of duplicated videos on youtube. Springer Journal of the Brazilian Computer Society, 16(3), 2010.Google Scholar
- F. Suchanek, G. Kasneci, and G. Weikum. Yago: a core of semantic knowledge. In Proc. World Wide Web Conference, 2007. Google ScholarDigital Library
- G. Szabo and B. Huberman. Predicting the popularity of online content. Communic. of ACM, 53(8), 2010. Google ScholarDigital Library
- F. Wu and B. Huberman. Novelty and collective attention. Proc. National Academy of Sciences, 104(45), 2007.Google Scholar
- T. Wu, M. Timmers, D. De Vleeschauwer, and W. Van Leekwijck. On the use of reservoir computing in popularity prediction. In Proc. Conference on Evolving Internet, 2010. Google ScholarDigital Library
- P. Yin, P. Luo, M. Wang, and W.-C. Lee. A straw shows which way the wind blows: Ranking potentially popular items from early votes. In Proc. WSDM 2012, 2012. Google ScholarDigital Library
Index Terms
- Using early view patterns to predict the popularity of youtube videos
Recommendations
Popularity Prediction of Videos in YouTube as Case Study: A Regression Analysis Study
BDCA'17: Proceedings of the 2nd international Conference on Big Data, Cloud and ApplicationsConsuming and watching videos in YouTube is an integral part of our daily lives. Predicting videos popularity is of great importance for many services and application ranging from supporting the design and evaluation of a wide range of systems, ...
Exploring the user-generated content (UGC) uploading behavior on youtube
WWW '14 Companion: Proceedings of the 23rd International Conference on World Wide WebYouTube is the world's largest video sharing platform where both professional and non-professional users participate in creating, uploading, and viewing content. In this work, we analyze content in the music category created by the non-professionals, ...
Early prediction of the future popularity of uploaded videos
Highlights- We propose a new approach to early prediction of new video popularity.
- Our ...
AbstractPredicting the popularity of videos on video sharing sites is important for the formulation of online advertising strategies and commercial marketing. The predicted popularity value can help the system decide which videos to recommend ...
Comments