Predicting the popularity of online articles based on user comments

A Tatar, J Leguay, P Antoniadis, A Limbourg… - Proceedings of the …, 2011 - dl.acm.org
A Tatar, J Leguay, P Antoniadis, A Limbourg, MD de Amorim, S Fdida
Proceedings of the International Conference on Web Intelligence, Mining and …, 2011dl.acm.org
Understanding user participation is fundamental in anticipating the popularity of online
content. In this paper, we explore how the number of users' comments during a short
observation period after publication can be used to predict the expected popularity of articles
published by a countrywide online newspaper. We evaluate a simple linear prediction
model on a real dataset of hundreds of thousands of articles and several millions of
comments collected over a period of four years. Analyzing the accuracy of our proposed …
Understanding user participation is fundamental in anticipating the popularity of online content. In this paper, we explore how the number of users' comments during a short observation period after publication can be used to predict the expected popularity of articles published by a countrywide online newspaper. We evaluate a simple linear prediction model on a real dataset of hundreds of thousands of articles and several millions of comments collected over a period of four years. Analyzing the accuracy of our proposed model for different values of its basic parameters we provide valuable insights on the potentials and limitations for predicting content popularity based on early user activity.
ACM Digital Library
以上显示的是最相近的搜索结果。 查看全部搜索结果