A review on web content popularity prediction: Issues and open challenges

• Tipo: Artigo em Revista Científica Internacional
• Data: 2019

Autores

Moniz, N (Autor) Outra; Torgo, L (Autor) FCUP

Revista

Título: Online Social Networks and Media

Vol. 12

Páginas: 1-20

Editora: Elsevier

Indexação

Scopus - 1 Citação

Outras Informações

ID Authenticus: P-00Q-PJJ

DOI: 10.1016/j.osnem.2019.05.002

Abstract (EN): With the profusion of web content, researchers have avidly studied and proposed new approaches to enable the anticipation of its impact on social media, presenting many distinct approaches throughout the last decade. Diverse approaches have been presented to tackle the problem of web content popularity prediction, including standard classification and regression approaches. Furthermore, these approaches have also taken into consideration distinct scenarios of data availability, where one may target the prediction of popularity before or after the publication of the items, which is highly interesting for different objectives from a user standpoint. This work aims at reviewing previous work and discussing open issues and challenges that could foster impactful research on this topic. Five areas are identified that require further research, covering the full spectrum of the problem: social media data, the learning task, recommendation and evaluation. © 2019 Elsevier B.V.

Idioma: Inglês

Tipo (Avaliação Docente): Científica