Predicting information cascade popularity is a fundamental problem in social networks.
Capturing temporal attributes and cascade role information (eg, cascade graphs and …

Abstract Information cascade size prediction is one of the primary challenges for
understanding the diffusion of information. Traditional feature‐based methods heavily rely …

The online social platforms, like Twitter, Facebook, LinkedIn and WeChat, have grown really
fast in last decade and have been one of the most effective platforms for people to …

Quantifying and predicting the long-term impact of both scientific papers and individual
authors have important implications for many academic policy decisions, from identifying …

A thorough understanding of the information dissemination process in Online Social
Networks (OSNs) is crucial for enhancing user behavior analysis. While recent studies …

In recent years, information popularity prediction of online social media plays a vital role in
crisis early warning and malicious content propagation identification within public opinion …

Predicting the future popularity of individual information cascades has attracted much
attention in various application fields. It is significantly important for online advertising, viral …

Predicting information diffusion cascade is an essential task in social networks. We mainly
focus on predicting the size of the information cascade. The relationships inside a cascade …

Predicting the popularity of information in social networks is crucial for effective social
marketing and recommendation systems. However, accurately comprehending the complex …

Predicting the information spread tendency can help products recommendation and public
opinion management. The existing information cascade prediction models are devoted to …