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Social Networking

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Decision model of public opinion risk in campus social network based on hybrid dynamic deletion and shortest path algorithm.

PloS one
Aiming at the problem that traditional network public opinion monitoring and searching are inefficient and can easily cause resource waste, the study firstly, through the dynamic deletion-shortest path algorithm to classify network text, and on this ...

Machine learning and deep learning-based approach to categorize Bengali comments on social networks using fused dataset.

PloS one
Through the advancement of the contemporary web and the rapid adoption of social media platforms such as YouTube, Twitter, and Facebook, for example, life has become much easier when dealing with certain highly personal problems. The far-reaching con...

Deep graph representation learning for influence maximization with accelerated inference.

Neural networks : the official journal of the International Neural Network Society
Selecting a set of initial users from a social network in order to maximize the envisaged number of influenced users is known as influence maximization (IM). Researchers have achieved significant advancements in the theoretical design and performance...

Bidirectional Long Short-Term Memory-Based Detection of Adverse Drug Reaction Posts Using Korean Social Networking Services Data: Deep Learning Approaches.

JMIR medical informatics
BACKGROUND: Social networking services (SNS) closely reflect the lives of individuals in modern society and generate large amounts of data. Previous studies have extracted drug information using relevant SNS data. In particular, it is important to de...

CoHet4Rec: A recommendation for collaborative heterogeneous information networks.

PloS one
Recommender Systems (RS) aim to predict users' latent interests in items by learning embeddings from user-item graphs. Graph Neural Networks (GNNs) have significantly advanced RS by enabling the embedding of graph-structured data. However, relying so...

How the technologies behind self-driving cars, social networks, ChatGPT, and DALL-E2 are changing structural biology.

BioEssays : news and reviews in molecular, cellular and developmental biology
The performance of deep Neural Networks (NNs) in the text (ChatGPT) and image (DALL-E2) domains has attracted worldwide attention. Convolutional NNs (CNNs), Large Language Models (LLMs), Denoising Diffusion Probabilistic Models (DDPMs)/Noise Conditio...

Predicting social anxiety disorder based on communication logs and social network data from a massively multiplayer online game: Using a graph neural network.

Psychiatry and clinical neurosciences
AIM: Social anxiety disorder (SAD) is a mental disorder that requires early detection and treatment. However, some individuals with SAD avoid face-to-face evaluations, which leads to delayed detection. We aim to predict individuals with SAD based on ...

Multi-level social network alignment via adversarial learning and graphlet modeling.

Neural networks : the official journal of the International Neural Network Society
Aiming to identify corresponding users in different networks, social network alignment is significant for numerous subsequent applications. Most existing models apply consistency assumptions on undirected networks, ignoring platform disparity caused ...

Hy-DeFake: Hypergraph neural networks for detecting fake news in online social networks.

Neural networks : the official journal of the International Neural Network Society
Nowadays social media is the primary platform for people to obtain news and share information. Combating online fake news has become an urgent task to reduce the damage it causes to society. Existing methods typically improve their fake news detectio...

Application of the LDA model to identify topics in telemedicine conversations on the X social network.

BMC health services research
The evolution experienced by global society, in the post-COVID 19 era, is marked by the quite obligatory use of digital media in many sectors, as is the case for the health sector. Quite frequently, both patients and health professionals use social m...