Today, computer systems hold large amounts of personal data. Yet while such an
abundance of data allows breakthroughs in artificial intelligence, and especially machine …

Though a fair amount of research is being done to address disinformation in online social
media, it has so far managed to stay ahead of the researchers' learning curves forcing the …

With recent advancements in graph neural networks (GNN), GNN-based recommender
systems (gRS) have achieved remarkable success in the past few years. Despite this …

Today's social networks continuously generate massive streams of data, which provide a
valuable starting point for the detection of rumours as soon as they start to propagate …

Advances in deep neural network (DNN) architectures have enabled new prediction
techniques for stock market data. Unlike other multivariate time-series data, stock markets …

Maximal subgraph mining is increasingly important in various domains, including
bioinformatics, genomics, and chemistry, as it helps identify common characteristics among …

Social media use has transformed communication and made social interaction more
accessible. Public microblogs allow people to share and access news through existing and …

As online social networks are experiencing extreme popularity growth, determining the
veracity of online statements denoted by rumors automatically as earliest as possible is …

With the development of the internet in China, information asymmetry in traditional
agriculture production has been alleviated, and the information on modern agricultural …

Aiming at the lack of feature extraction ability of rumor detection methods based on the deep
learning model, this study proposes a rumor detection method based on deep learning in …