Convex Optimization
Yago: a core of semantic knowledge
Proceedings of the 16th international conference on World Wide Web
I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Analyzing the video popularity characteristics of large-scale user generated content systems
IEEE/ACM Transactions on Networking (TON)
Using a model of social dynamics to predict popularity of news
Proceedings of the 19th international conference on World wide web
Predicting the popularity of online content
Communications of the ACM
On Popularity in the Blogosphere
IEEE Internet Computing
An Approach to Model and Predict the Popularity of Online Contents with Explanatory Factors
WI-IAT '10 Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
The tube over time: characterizing popularity growth of youtube videos
Proceedings of the fourth ACM international conference on Web search and data mining
A straw shows which way the wind blows: ranking potentially popular items from early votes
Proceedings of the fifth ACM international conference on Web search and data mining
On the prediction of popularity of trends and hits for user generated videos
Proceedings of the sixth ACM international conference on Web search and data mining
Demystifying porn 2.0: a look into a major adult video streaming website
Proceedings of the 2013 conference on Internet measurement conference
On popularity prediction of videos shared in online social networks
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Characterizing the life cycle of online news stories using social media reactions
Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing
Inferring the impacts of social media on crowdfunding
Proceedings of the 7th ACM international conference on Web search and data mining
Who watches (and shares) what on youtube? and when?: using twitter to understand youtube viewership
Proceedings of the 7th ACM international conference on Web search and data mining
Proceedings of the 23rd international conference on World wide web
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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.