Effective and effortless features for popularity prediction in microblogging network
Shuai Gao, Jun Ma, Zhumin Chen · 2014
Predicting popularity of online contents is of remarkable practical value in various business and administrative applications. Existing studies mainly focus on finding the most effective features for prediction. However, some effective features, such as structural features which are extracted from the underlying user network, are hard to access. In this paper, we aim to identify features that are both effective and effortless (easy to obtain or compute). Experiments on Sina Weibo show the effectiveness and effortlessness of the temporal features and satisfying prediction performance can be obtained based on only the temporal features of first 10 retweets.