Social media networks have become a significant aspect of people's lives, serving as a
platform for their ideas, opinions and emotions. Consequently, automated sentiment …

Multimodal data can convey user emotions and feelings more effectively and interactively
than unimodal content. Thus, multimodal sentiment analysis (MSA) research has recently …

The increasing popularity of social networks and users' tendency towards sharing their
feelings, expressions, and opinions in text, visual, and audio content have opened new …

Visual sentiment analysis aims to predict human emotional responses to visual stimuli. It has
attracted considerable attention owing to the increasing popularity of online image sharing …

Multimodal Sentiment Analysis (SA) is gaining popularity due to its broad application
potential. The existing studies have focused on the SA of single modalities, such as texts or …

Recently, multi-modal affective computing has demonstrated that introducing multi-modal
information can enhance performance. However, multi-modal research faces significant …

Different parts of an image have a strong or weak guiding effect on emotions. The key to
emotion recognition of images is to fully exploit the regions associated with emotions …

Recently, video sentiment computing has become the focus of research because of its
benefits in many applications such as digital marketing, education, healthcare, and so on …

Incorporating visual attributes such as objects and scene features into deep models has
been proved valuable for affective image recognition. In general, the existing works achieve …

The image emotion classification task aims to use the model to automatically predict the
emotional response of people when they see the image. Studies have shown that certain …