Social network analysis using deep learning: applications and schemes
AM Abbas - Social Network Analysis and Mining, 2021 - Springer
Online social networks (OSNs) are part of daily life of human beings. Millions of users are
connected through online social networks. Due to very large number of users and huge …
connected through online social networks. Due to very large number of users and huge …
Decoding the silent majority: Inducing belief augmented social graph with large language model for response forecasting
Automatic response forecasting for news media plays a crucial role in enabling content
producers to efficiently predict the impact of news releases and prevent unexpected …
producers to efficiently predict the impact of news releases and prevent unexpected …
Unsupervised belief representation learning with information-theoretic variational graph auto-encoders
This paper develops a novel unsupervised algorithm for belief representation learning in
polarized networks that (i) uncovers the latent dimensions of the underlying belief space and …
polarized networks that (i) uncovers the latent dimensions of the underlying belief space and …
Using multi-dimensional dynamic time warping to identify time-varying lead-lag relationships
J Stübinger, D Walter - Sensors, 2022 - mdpi.com
This paper develops a multi-dimensional Dynamic Time Warping (DTW) algorithm to identify
varying lead-lag relationships between two different time series. Specifically, this manuscript …
varying lead-lag relationships between two different time series. Specifically, this manuscript …
[HTML][HTML] A review of feature fusion-based media popularity prediction methods
With the popularization of social media, the way of information transmission has changed,
and the prediction of information popularity based on social media platforms has attracted …
and the prediction of information popularity based on social media platforms has attracted …
Sentiment and hashtag-aware attentive deep neural network for multimodal post popularity prediction
Social media users articulate their opinions on a broad spectrum of subjects and share their
experiences through posts comprising multiple modes of expression, leading to a notable …
experiences through posts comprising multiple modes of expression, leading to a notable …
Unsupervised image classification by ideological affiliation from user-content interaction patterns
The proliferation of political memes in modern information campaigns calls for efficient
solutions for image classification by ideological affiliation. While significant advances have …
solutions for image classification by ideological affiliation. While significant advances have …
Signed Graph Representation Learning: A Survey
With the prevalence of social media, the connectedness between people has been greatly
enhanced. Real-world relations between users on social media are often not limited to …
enhanced. Real-world relations between users on social media are often not limited to …
Which is better? A modularized evaluation for topic popularity prediction
The purpose of topic popularity prediction is to predict whether a topic on the Internet will
become popular. Various elegant models have been proposed for this problem. However …
become popular. Various elegant models have been proposed for this problem. However …
Jointly predicting future content in multiple social media sites based on multi-task learning
User-generated contents (UGC) in social media are the direct expression of users' interests,
preferences, and opinions. User behavior prediction based on UGC has increasingly been …
preferences, and opinions. User behavior prediction based on UGC has increasingly been …