AIMC Topic: Social Media

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Exploring the Chinese Public's Perception of Omicron Variants on Social Media: LDA-Based Topic Modeling and Sentiment Analysis.

International journal of environmental research and public health
The COVID-19 pandemic caused by SARS-CoV-2 is still raging. Similar to other RNA viruses, SARS-COV-2 is constantly mutating, which leads to the production of many infectious and lethal strains. For instance, the omicron variant detected in November 2...

Sentiment Analysis of Image with Text Caption using Deep Learning Techniques.

Computational intelligence and neuroscience
People are actively expressing their views and opinions via the use of visual pictures and text captions on social media platforms, rather than just publishing them in plain text as a consequence of technical improvements in this field. With the adve...

From YouTube to the brain: Transfer learning can improve brain-imaging predictions with deep learning.

Neural networks : the official journal of the International Neural Network Society
Deep learning has recently achieved best-in-class performance in several fields, including biomedical domains such as X-ray images. Yet, data scarcity poses a strict limit on training successful deep learning systems in many, if not most, biomedical ...

Visual Sentiment Analysis With Social Relations-Guided Multiattention Networks.

IEEE transactions on cybernetics
These days, social media users tend to express their feelings through sharing images online. Capturing the emotions embedded in these social images involves great research challenges and practical values. Most existing works concentrate on extracting...

Deep Learning Approaches for Cyberbullying Detection and Classification on Social Media.

Computational intelligence and neuroscience
As a result of the ease with which the internet and cell phones can be accessed, online social networks (OSN) and social media have seen a significant increase in popularity in recent years. Security and privacy, on the other hand, are the key concer...

Joint Stance and Rumor Detection in Hierarchical Heterogeneous Graph.

IEEE transactions on neural networks and learning systems
Recently, large volumes of false or unverified information (e.g., fake news and rumors) appear frequently in emerging social media, which are often discussed on a large scale and widely disseminated, causing bad consequences. Many studies on rumor de...

Social impact and governance of AI and neurotechnologies.

Neural networks : the official journal of the International Neural Network Society
Advances in artificial intelligence (AI) and brain science are going to have a huge impact on society. While technologies based on those advances can provide enormous social benefits, adoption of new technologies poses various risks. This article fir...

Aspect Based Twitter Sentiment Analysis on Vaccination and Vaccine Types in COVID-19 Pandemic With Deep Learning.

IEEE journal of biomedical and health informatics
Due to the COVID-19 pandemic, vaccine development and community vaccination studies are carried out all over the world. At this stage, the opposition to the vaccine seen in the society or the lack of trust in the developed vaccine is an important fac...

An Improved BERT and Syntactic Dependency Representation Model for Sentiment Analysis.

Computational intelligence and neuroscience
Text representation of social media is an important task for users' sentiment analysis. Utilizing the better representation, we can accurately acquire the real semantic information expressed by online users. However, existing works cannot achieve the...

English Text Recognition Deep Learning Framework to Automatically Identify Fake News.

Computational intelligence and neuroscience
Fake news spreading rapidly worldwide is considered one of the most severe problems of modern technology that needs to be addressed immediately. The remarkable increase in the use of social media as a critical source of information combined with the ...