Link prediction finds missing links (in static networks) or predicts the likelihood of future links
(in dynamic networks). The latter definition is useful in network evolution (Wang et al., 2011; …

Link prediction methods anticipate the likelihood of a future connection between two nodes
in a given network. The methods are essential in social networks to infer social interactions …

Twitter is the third most popular worldwide Online Social Network (OSN) after Facebook and
Instagram. Compared to other OSNs, it has a simple data model and a straightforward data …

With the recent advances in the field of artificial intelligence, an increasing number of
decision-making tasks are delegated to software systems. A key requirement for the success …

Network embedding leverages the node proximity manifested to learn a low-dimensional
node vector representation for each node in the network. The learned embeddings could …

Link prediction is a paradigmatic problem in network science, which aims at estimating the
existence likelihoods of nonobserved links, based on known topology. After a brief …

Background: Online health communities (OHCs) have become a major source of social
support for people with health problems. Members of OHCs interact online with similar peers …

Numerous studies have been conducted to investigate the properties of large-scale
temporal graphs. Despite the ubiquity of these graphs in real-world scenarios, it's usually …

The effects of online social media on critical issues, such as polarization and misinformation,
are under scrutiny due to the disruptive consequences that these phenomena can have on …

Effectively detecting anomalous nodes in attributed networks is crucial for the success of
many real-world applications such as fraud and intrusion detection. Existing approaches …