Skip to Main content Skip to Navigation
Journal articles

A survey on predicting the popularity of web content.

Abstract : Social media platforms have democratized the process of web content creation allowing mere consumers to become creators and distributors of content. But this has also contributed to an explosive growth of information and has intensified the online competition for users attention, since only a small number of items become popular while the rest remain unknown. Understanding what makes one item more popular than another, observing its popularity dynamics, and being able to predict its popularity has thus attracted a lot of interest in the past few years. Predicting the popularity of web content is useful in many areas such as network dimensioning (e.g., caching and replication), online marketing (e.g., recommendation systems and media advertising), or real-world outcome prediction (e.g., economical trends). In this survey, we review the current findings on web content popularity prediction. We describe the different popularity prediction models, present the features that have shown good predictive capabilities, and reveal factors known to influence web content popularity.
Complete list of metadatas

https://hal.archives-ouvertes.fr/hal-01137930
Contributor : Maura Covaci <>
Submitted on : Tuesday, March 31, 2015 - 5:08:28 PM
Last modification on : Wednesday, May 6, 2020 - 4:34:29 PM

Links full text

Identifiers

Citation

Alexandru Tatar, Marcelo Dias de Amorim, Serge Fdida, Panayotis Antoniadis. A survey on predicting the popularity of web content.. Journal of Internet Services and Applications, Springer, 2014, 5 (1), pp.8. ⟨10.1186/s13174-014-0008-y⟩. ⟨hal-01137930⟩

Share

Metrics

Record views

625