AIMC Topic: Social Networking

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A retail investor in a cobweb of social networks.

PloS one
In this study, using AI, we empirically examine the irrational behaviour, specifically attention-driven trading and emotion-driven trading such as consensus trading, of retail investors in an emerging stock market. We used a neural network to assess ...

Year 2021: COVID-19, Information Extraction and BERTization among the Hottest Topics in Medical Natural Language Processing.

Yearbook of medical informatics
OBJECTIVES: Analyze the content of publications within the medical natural language processing (NLP) domain in 2021.

A New Consensus Model Based on Trust Interactive Weights for Intuitionistic Group Decision Making in Social Networks.

IEEE transactions on cybernetics
A promising feature for group decision making (GDM) lies in the study of the interaction between individuals. In conventional GDM research, experts are independent. This is reflected in the setting of preferences and weights. Nevertheless, each exper...

Semisupervised neural biomedical sense disambiguation approach for aspect-based sentiment analysis on social networks.

Journal of biomedical informatics
Patient narratives on social networks contain large amounts of objective information, such as the descriptions of examinations and interventions. Sentiment analysis (SA) models are mostly used to evaluate the conveyed sentiments by patients in these ...

Security Analysis of Social Network Topic Mining Using Big Data and Optimized Deep Convolutional Neural Network.

Computational intelligence and neuroscience
This research aims to conduct topic mining and data analysis of social network security using social network big data. At present, the main problem is that users' behavior on social networks may reveal their private data. The main contribution lies i...

A Graph-Neural-Network-Based Social Network Recommendation Algorithm Using High-Order Neighbor Information.

Sensors (Basel, Switzerland)
Social-network-based recommendation algorithms leverage rich social network information to alleviate the problem of data sparsity and boost the recommendation performance. However, traditional social-network-based recommendation algorithms ignore hig...

CAMU: Cycle-Consistent Adversarial Mapping Model for User Alignment Across Social Networks.

IEEE transactions on cybernetics
The user alignment problem that establishes a correspondence between users across networks is a fundamental issue in various social network analyses and applications. Since symbolic representations of users suffer from sparsity and noise when computi...

Grading Nursing Care Study in Integrated Medical and Nursing Care Institution Based on Two-Stage Gray Synthetic Clustering Model under Social Network Context.

International journal of environmental research and public health
Establishing a scientific and sustainable grading nursing care evaluation system is the key to realizing the rational distribution of medical and nursing resources in the combined medical and nursing care services. This study establishes a grading nu...

Language-agnostic deep learning framework for automatic monitoring of population-level mental health from social networks.

Journal of biomedical informatics
In many countries, mental health issues are among the most serious public health concerns. National mental health statistics are frequently collected from reported patient cases or government-sponsored surveys, which have restricted coverage, frequen...

Let's (Tik) Talk About Fitness Trends.

Frontiers in public health
Several factors that follow the development of society affect physical inactivity, which primarily includes the development of technology and digitalization and the increasing choice of unhealthy lifestyle habits. However, certain shifts in the fitne...