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Predicting popularity trend in social media networks with multi-layer temporal graph neural networks
Predicting what becomes popular on social media is crucial because it helps us understand future topics and public interests based on massive social...
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Toward rumor detection in social networks using multi-layer autoencoder neural network
In recent years, the issue of spreading rumors as a big challenge in social networks has attracted a lot of attention. The spread of rumors on social...
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Linking perspectives: a field experiment on the role of multi-layer networks in refugee information sharing
The social networks that interconnect groups of people are often “multi-layered”—comprised of a variety of relationships and interaction types....
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A new multi-wave continuous action-set cellular learning automata for link prediction problem in weighted multi-layer social networks
One of the main research areas in social network analysis (SNA) is link prediction (LP). Social networks can be shown as a graph, and LP algorithms...
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Predicting COVID-19 infections using multi-layer centrality measures in population-scale networks
Understanding the spread of SARS-CoV-2 has been one of the most pressing problems of the recent past. Network models present a potent approach to...
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A novel clustering algorithm based on multi-layer features and graph attention networks
Clustering is a fundamental task in the field of data analysis. With the development of deep learning, deep clustering focuses on learning meaningful...
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How Information Spreads Through Multi-layer Networks: A Case Study of Rural Uganda
The social networks that interconnect groups of people are often “multi-layered"– comprised of a variety of relationships and interaction types....
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A continuous-time diffusion model for inferring multi-layer diffusion networks
Inferring multilayer diffusion networks from observed cascades is both crucial and realistic. To infer multilayer diffusion networks, constructing...
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Recommendation System over Multi-layer Complex Networks: A Wide and Deep Graph Convolutional Neural Network Approach
In recent years, the design of recommendation systems has emerged as a trending, yet challenging topic. Concurrently, there has been a significant...
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Multi-layer, multi-modal medical image intelligent fusion
Recently, deep learning has high popularity in the field of image processing due to its unique feature extraction property. This paper, proposes a...
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A comprehensive view of community detection approaches in multilayer social networks
Multilayer social networks are the main representative form for today’s social networks. In fact, the multiplicity of relations, the huge amount of...
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Null Models and Community Detection in Multi-Layer Networks
Multi-layer networks of multiplex type represent relational data on a set of entities (nodes) with multiple types of relations (edges) among them...
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Real-time updating of dynamic social networks for COVID-19 vaccination strategies
Vaccination strategy is crucial in fighting the COVID-19 pandemic. Since the supply is still limited in many countries, contact network-based...
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Interpretable Cross-Platform Coordination Detection on Social Networks
Numerous disinformation campaigns are operating on social networks to influence public opinion. Detecting these campaigns primarily involves...
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An effective keyword search co-occurrence multi-layer graph mining approach
A combination of tools and methods known as "graph mining" is used to evaluate real-world graphs, forecast the potential effects of a given graph’s...
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Trust assessment in social networks
Social network interactions and web/IoT-based applications have led to data getting generated at a very rapid rate. Amongst these, social networking...
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Multi-layer network approach in modeling epidemics in an urban town
AbstractThe last three years have been an extraordinary time with the COVID-19 pandemic killing millions, affecting and distressing billions of...
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An effective link prediction method in multiplex social networks using local random walk towards dependable pathways
Link Prediction Problem (LPP) is defined as the likelihood of a future connection between two nodes on a network that does not currently have a link...
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Exploiting social graph networks for emotion prediction
Emotion prediction plays an essential role in mental healthcare and emotion-aware computing. The complex nature of emotion resulting from its...
