When available, multimodal data is key for enhanced emotion recognition in conversation.
Text, audio, and video in dialogues can facilitate and complement each other in analyzing …

Sentiment analysis is a computational technique that analyses the subjective information
conveyed within a given expression. This encompasses appraisals, opinions, attitudes or …

Compared with single-modal content, multimodal data can express users' feelings and
sentiments more vividly and interestingly. Therefore, multimodal sentiment analysis has …

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 …

To exactly classify sentiments of microblog reviews with emojis in microblog social networks,
this paper first proposes an emoji vectorisation method to achieve emoji vectors. Then, an …

Sentiment analysis of social multimedia data has attracted extensive research interest and
has been applied to many tasks, such as election prediction and products evaluation …

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

Social networking platforms have witnessed tremendous growth of textual, visual, audio, and
mix-mode contents for expressing the views or opinions. Henceforth, Sentiment Analysis …

Social media users are increasingly turning to express opinions with both images and text,
while the visual content and text description may cover some conflicting information diverse …

Multimodal sentiment analysis has attracted increasing attention with broad application
prospects. Most of the existing methods have focused on a single modality, which fails to …