A survey of information cascade analysis: Models, predictions, and recent advances
The deluge of digital information in our daily life—from user-generated content, such as
microblogs and scientific papers, to online business, such as viral marketing and advertising …
microblogs and scientific papers, to online business, such as viral marketing and advertising …
[HTML][HTML] CasSeqGCN: Combining network structure and temporal sequence to predict information cascades
One important task in the study of information cascade is to predict the future recipients of a
message given its past spreading trajectory. While the network structure serves as the …
message given its past spreading trajectory. While the network structure serves as the …
Personalized DeepInf: enhanced social influence prediction with deep learning and transfer learning
CK Leung, A Cuzzocrea, JJ Mai… - … conference on big …, 2019 - ieeexplore.ieee.org
Social influence is referred to as the phenomenon that one's opinions or behaviors be
affected by others. Nowadays, the potential impact of social influence analysis (SIA) is …
affected by others. Nowadays, the potential impact of social influence analysis (SIA) is …
Casflow: Exploring hierarchical structures and propagation uncertainty for cascade prediction
Understanding in-network information diffusion is a fundamental problem in many
applications and one of the primary challenges is to predict the information cascade size …
applications and one of the primary challenges is to predict the information cascade size …
An invertible graph diffusion neural network for source localization
Localizing the source of graph diffusion phenomena, such as misinformation propagation, is
an important yet extremely challenging task in the real world. Existing source localization …
an important yet extremely challenging task in the real world. Existing source localization …
Variational information diffusion for probabilistic cascades prediction
Understanding in-network information diffusion is a fundamental problem in many
application domains and one of the primary challenges is to predict the size of the …
application domains and one of the primary challenges is to predict the size of the …
Graph representation learning for popularity prediction problem: a survey
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 …
fast in last decade and have been one of the most effective platforms for people to …
Predicting viral rumors and vulnerable users with graph-based neural multi-task learning for infodemic surveillance
In the age of the infodemic, it is crucial to have tools for effectively monitoring the spread of
rampant rumors that can quickly go viral, as well as identifying vulnerable users who may be …
rampant rumors that can quickly go viral, as well as identifying vulnerable users who may be …
On the challenges of predicting microscopic dynamics of online conversations
To what extent can we predict the structure of online conversation trees? We present a
generative model to predict the size and evolution of threaded conversations on social …
generative model to predict the size and evolution of threaded conversations on social …
[HTML][HTML] A Survey of Deep Learning-Based Information Cascade Prediction
Z Wang, X Wang, F Xiong, H Chen - Symmetry, 2024 - mdpi.com
Online social media have significantly boosted the creation and transmission of information,
accelerating the dissemination and interaction of vast amounts of data, thereby making the …
accelerating the dissemination and interaction of vast amounts of data, thereby making the …