Why cannot long-term cascade be predicted? Exploring temporal dynamics in information diffusion processes.

ABSTRACT: Predicting information cascade plays a crucial role in various applications such as advertising campaigns, emergency management and infodemic controlling. However, predicting the scale of an information cascade in the long-term could be difficult. In this study, we take Weibo, a Twitter-like online social platform, as an example, exhaustively extract predictive features from the data, and use a conventional machine learning algorithm to predict the information cascade scales. Specifically, we compare the predictive power (and the loss of it) of different categories of features in short-term and long-term prediction tasks. Among the features that describe the user following network, retweeting network, tweet content and early diffusion dynamics, we find that early diffusion dynamics are the

SUBMITTER: Cao RM 

PROVIDER: S-EPMC8437228 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature