The prosperity of e-commerce enables the public or consumers to generate a large number of multi-modal multimedia information such as comments, likes, emoticons, and ratings for products or services. The most significant feature of this information is that it fully displays the psychological and emotional characteristics of users. Negative review texts, sad memes, and low product ratings and likes will be left if the user's post-purchase experience of a product is very poor. Such information is widely available on various e-commerce platforms, news websites, forums, and social media, such as Amazon, Alibaba, Jingdong Mall, and Twitter. Since this multi-modal multimedia information with users' psychological emotions fully depicts the deficiencies of products or services, they not only become the basis for consumers to make online purchase decisions, but also provide decision support for merchants to improve and innovate their services or products.

In the era of the Internet economy, the diversification and heterogeneity of consumers aggravate the difficulty of enterprise product innovation, but also provide an information basis for enterprises to perceive innovation opportunities from the perspective of consumers. For enterprises, users' multi-modal multimedia information not only contains consumers' experiences and feelings but also can provide objective and reliable product evaluation based on the perspective of consumers, especially the identification and rejection of each product feature in psychological and emotional aspects. These psychological emotions are exactly the important direction of continuous product improvement and innovation of enterprises, which help enterprises to understand consumer demand, grasp market, and technology dynamics, and tap market opportunities and product innovation direction. Therefore, the strengths and weaknesses of online products can be mined from users' multi-modal multimedia information, and the research and development strategies of subsequent products can be adjusted according to multi-modal multimedia information, to keep the dominant position of enterprises in the increasingly fierce market competition.

This Special Issue aims to seek high-quality original research and review articles on the extensions and applications of online product decision analysis using multi-modal multimedia information. We sincerely hope that this Issue provides a platform for researchers in various areas to exchange ideas on how we can further develop and apply advanced methods to address the problems of online product decisions based on multi-modal multimedia information.

Potential topics include but are not limited to the following:

• Data analytics of multi-modal multimedia information with users' psychological emotions in e-commerce
• Feature extraction and representation of multi-modal multimedia information with users' psychological emotions in e-commerce
• Multi-modal multimedia information clustering with users' psychological emotions in e-commerce
• Multi-modal multimedia information fusion with users' psychological emotions in e-commerce
• False multi-modal multimedia information recognition with users' psychological emotions in e-commerce
• Online shopping decisions based on multi-modal multimedia information with users' psychological emotions in e-commerce
• Online product improvement based on multi-modal multimedia information with users' psychological emotions in e-commerce
• Optimizing online product display layout in e-commerce platform driven by multi-modal multimedia information with users' psychological emotions in e-commerce
• Intelligent online product decision support systems enabled by multi-modal multimedia information with users' psychological emotions in e-commerce
• Advanced algorithms for multi-modal multimedia data-driven online product decisions in e-commerce