Cross-domain sentiment analysis (CDSA) aims to predict the sentiment polarities of reviews
in the target domain using a sentiment classifier learned from the source labeled domain …

Multimodal sentiment analysis aims to effectively integrate information from various sources
to infer sentiment, where in many cases there are no annotations for unimodal labels …

Existing multimodal sentiment analysis models focus more on fusing highly correlated image-
text pairs, and thus achieves unsatisfactory performance on multimodal social media data …

Social media platforms, rich in user-generated content, offer a unique perspective on public
opinion, making stance detection an essential task in opinion mining. However, traditional …

In open environments, multimodal sentiment analysis (MSA) often suffers from low-quality
data and can be disrupted by noise, inherent defects, and outliers. In some cases …

The rise of fake news presents a critical challenge to societal stability, emphasizing the
urgent need for efficient detection systems. This study introduces an innovative approach to …

Sentiment analysis has historically concentrated on text-based data to investigate people's
views towards objects. However, given how frequently visual content is shared on social …

With the exponential growth of e-commerce, understanding consumer sentiments from
online product reviews has become crucial for businesses. This study presents a …

Social media platforms like Facebook play a pivotal role in facilitating mass communication,
opinion expression, and information sharing, generating extensive unstructured data …

Content generation has been identifies as a key challenge in a social network. As the social
network is being in a peak in the human society, generating content according to the …