A comprehensive survey on deep graph representation learning
Graph representation learning aims to effectively encode high-dimensional sparse graph-
structured data into low-dimensional dense vectors, which is a fundamental task that has …
structured data into low-dimensional dense vectors, which is a fundamental task that has …
[HTML][HTML] A survey on deep learning for textual emotion analysis in social networks
S Peng, L Cao, Y Zhou, Z Ouyang, A Yang, X Li… - Digital Communications …, 2022 - Elsevier
Abstract Textual Emotion Analysis (TEA) aims to extract and analyze user emotional states
in texts. Various Deep Learning (DL) methods have developed rapidly, and they have …
in texts. Various Deep Learning (DL) methods have developed rapidly, and they have …
A metaverse: Taxonomy, components, applications, and open challenges
SM Park, YG Kim - IEEE access, 2022 - ieeexplore.ieee.org
Unlike previous studies on the Metaverse based on Second Life, the current Metaverse is
based on the social value of Generation Z that online and offline selves are not different …
based on the social value of Generation Z that online and offline selves are not different …
[HTML][HTML] User OCEAN personality model construction method using a BP neural network
Highlights What are the main findings? First, the combination of the methods of machine
learning with psychological methods to predict the user's OCEAN personality model could …
learning with psychological methods to predict the user's OCEAN personality model could …
The fractal dimension of complex networks: A review
The fractal property is one of the most important properties in complex networks. It describes
the power law relationship between characteristics of the box and the box size. There are …
the power law relationship between characteristics of the box and the box size. There are …
Community detection algorithms in healthcare applications: a systematic review
Over the past few years, the number and volume of data sources in healthcare databases
has grown exponentially. Analyzing these voluminous medical data is both opportunity and …
has grown exponentially. Analyzing these voluminous medical data is both opportunity and …
Lies kill, facts save: Detecting COVID-19 misinformation in twitter
MS Al-Rakhami, AM Al-Amri - Ieee Access, 2020 - ieeexplore.ieee.org
Online social networks (ONSs) such as Twitter have grown to be very useful tools for the
dissemination of information. However, they have also become a fertile ground for the …
dissemination of information. However, they have also become a fertile ground for the …
Mapping of machine learning approaches for description, prediction, and causal inference in the social and health sciences
Machine learning (ML) methodology used in the social and health sciences needs to fit the
intended research purposes of description, prediction, or causal inference. This paper …
intended research purposes of description, prediction, or causal inference. This paper …
A framework for anomaly detection and classification in Multiple IoT scenarios
The investigation of anomalies is an important element in many scientific research fields. In
recent years, this activity has been also extended to social networking and social …
recent years, this activity has been also extended to social networking and social …
Multi-perspectives systematic review on the applications of sentiment analysis for vaccine hesitancy
A substantial impediment to widespread Coronavirus disease (COVID-19) vaccination is
vaccine hesitancy. Many researchers across scientific disciplines have presented countless …
vaccine hesitancy. Many researchers across scientific disciplines have presented countless …