Utilizing visualization techniques for opinion mining and sentiment exploration of social media texts is a pivotal concern in the visualization field. Research predominantly concentrates on the collective expression of numerous users on popular topics within the public domain. However, there is a need to focus on changing or evolving sentiments for individuals. This paper tries to integrate sentiment analysis with visualization techniques to enable individual users to visually explore the underlying sentiment stories behind their social media texts. Therefore, the SentiSand system is designed and developed based on user requirements. It employs innovative visual design to transform the text from users' social media into a series of visual stories to facilitate users tracking their sentiment changes. The system provides the functionalities of visualizing the overview of the sentiment evolution over a specified period, the sentiment polarity distribution, and words used over that period as well. In a user study, eighteen participants with diverse backgrounds are invited to evaluate the system. The results demonstrate that SentiSand can effectively and intuitively depict sentiment states and changes. All participants gave the system high ratings across dimensions of creativity, practicality, and narrative coherence. Overall, this paper introduces a novel perspective and methodology for visualizing personal sentiments, thereby contributing to an enhanced comprehension of and intervention in individual sentiment states.

In the digital era, traditional methods of historical learning are undergoing a transition, as there is a growing demand for intuitive and visually engaging approaches. Vi-sualization, particularly timeline-based visualization, is critical in bridging the gap between extensive and complex historical events and history learners due to its intuitive features. Despite the advances in existing timeline visualization tools, they often face challenges: visualization creators spend much time in the materials preparation stage, especially for designers unfamiliar with the history; the lack of flexible interaction limits users from designing customized representations, which decreases the user's interest. To address these issues, we have developed Create3DHistory, a system that leverages the advanced Artificial Intelligence Generated Content and visualization technologies, enabling users to easily generate historical events content and create 3D and 2D historical event timeline representation. Users only need to input the name of a historical event, and the system will automatically generate corresponding content and deploy it onto the timeline representation. Moreover, users can edit the generated content or upload self-prepared multimedia materials for customized event visualization. The user study has demonstrated that Create3DHistory can effectively assist users in customizing personalized historical event timelines. Overall, the proposed tool simplifies the timeline creation process using AIGC technology, providing an overview and detailed information on-demand functions for various tasks.

Digital humanity visualization, as an innovative trend that combines historical and cultural studies with visualization, aims to provide the public with intuitive and engaging cultural exploration experiences. However, it is still challenging in this field due to the intrinsic complex and cumbersome textual data, such as how to intuitively and comprehensively present complex relationship networks and spatiotemporal evolution among the data. In this paper, we take the Jinling-related dataset as an example to design a composite visual storytelling tool that utilizes a narrative framework that smoothly changes between macro and micro perspectives. Simultaneously, AI-generated intuitive images are employed to represent the textual data, collectively narrating an engaging cultural story of Jinling. Through user studies, we validate the effectiveness and usability of the tool and demonstrate that the tool possesses excellent storytelling capabilities to improve users' cultural experiences.

The digitization of cultural heritage offers opportunities for preservation and dissemination but also presents challenges in fostering public engagement and narrative coherence. This paper proposes an interactive storytelling system that integrates AI technologies, including AI agents, LLMs, and visualization tools, to enhance user engagement with cultural heritage. Using the Jataka story murals from the Dunhuang grottoes as a case study, the proposed system features three core modules: mural segmentation with cultural context explanations, an interactive knowledge graph that enables users to engage with the murals through storytelling, and user-driven creative reconstruction through comic-style narratives. An AI agent supports these modules by offering conversational interactions that provide real-time explanations, personalized guidance, and creative suggestions. User evaluations based on the User Experience Questionnaire demonstrate the system’s effectiveness in promoting user engagement, with particularly high scores in attractiveness, novelty, and stimulation. These results suggest that the system increases accessibility and interactivity, helping users form deeper emotional and intellectual connections with cultural heritage. The prototype system demonstrates the framework’s potential to make cultural heritage more accessible and participatory, fostering richer connections through interaction, storytelling, and creative expression. These findings highlight the potential of this approach to connect traditional heritage with contemporary audiences, offering new avenues for participation, learning, and creative engagement.

This paper aims to explore the use of color and color harmony in Vincent van Gogh’s paintings and present the results in the form of a web-based digital museum to provide an intuitive and immersive experience to the public audience. To achieve this goal, we tested four different color extraction algorithms and determined the extcolors library to be the most effective method for extracting theme colors after interviewing ten random viewers. This study then conducted a visual analysis of the extracted colors, revealing that the predominant colors of van Gogh’s paintings were yellow and green, followed by blue and red. We also identified the main types of color harmony used in van Gogh’s paintings as monochromatic, analogous, and complementary harmony. The ultimate outcome of this research is a digital gallery that showcases the different periods of van Gogh’s work via a timeline representation, highlighting the distinctive color schemes that were employed during each period. This presentation gives the exhibits a clear context and provides the viewer with a clear and vivid experience. Overall, the study’s findings reveal insightful information about how color is employed in van Gogh’s artwork and suggest a useful application which is in the form of a timeline representation that can be used to improve the audience’s exposure to the art and cultural heritage.