EmoBalloon - Conveying Emotional Arousal in Text Chats with Speech Balloons

Aoki, Toshiki; Chujo, Rintaro; Matsui, Katsufumi; Choi, Saemi; Hautasaari, Ari

doi:10.1145/3491102.3501920

Cited by 22 publications

(7 citation statements)

References 40 publications

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“…Expressing emotion has been widely studied in the humancomputer interaction community [47], [69], covering design elements including pattern [68], texture [13], typeface [52], font style [26], speech balloon shape [3], and generative art [31]. Recent years have witnessed increasing scholarly attention to the emotional dimension of data visualization [42], [74].…”

Section: Affective Visualization Designmentioning

confidence: 99%

Creating Emordle: Animating Word Cloud for Emotion Expression

Xie

Shu

et al. 2024

IEEE Trans. Visual. Comput. Graphics

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We propose emordle, a conceptual design that animates wordles (compact word clouds) to deliver their emotional context to audiences. To inform the design, we first reviewed online examples of animated texts and animated wordles, and summarized strategies for injecting emotion into the animations. We introduced a composite approach that extends an existing animation scheme for one word to multiple words in a wordle with two global factors: the randomness of text animation (entropy) and the animation speed (speed). To create an emordle, general users can choose one predefined animated scheme that matches the intended emotion class and fine-tune the emotion intensity with the two parameters. We designed proof-of-concept emordle examples for four basic emotion classes, namely happiness, sadness, anger, and fear. We conducted two controlled crowdsourcing studies to evaluate our approach. The first study confirmed that people generally agreed on the conveyed emotions from well-crafted animations, and the second one demonstrated that our identified factors helped fine-tune the extent of the emotion delivered. We also invited general users to create their own emordles based on our proposed framework. Through this user study, we confirmed the effectiveness of the approach. We concluded with implications for future research opportunities of supporting emotion expression in visualizations.

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Section: Affective Visualization Designmentioning

confidence: 99%

Creating Emordle: Animating Word Cloud for Emotion Expression

Xie

Shu

et al. 2024

IEEE Trans. Visual. Comput. Graphics

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“…To make it attentive to emotional changes in narratives for G1, two different shapes were designed to distinguish literal and metaphorical scenes. As informed by [3], we assumed that spiky text bubbles imply higher emotional arousal than rounded ones. Therefore, we use spiky text bubbles for metaphorical scenes, and rounded bubbles for literal scenes, as shown in Figure 5.…”

Section: Text Bubble and Metaphormentioning

confidence: 99%

Metamorpheus: Interactive, Affective, and Creative Dream Narration Through Metaphorical Visual Storytelling

Wan,

Feng,

Bei

et al. 2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

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Human emotions are essentially molded by lived experiences, from which we construct personalised meaning. The engagement in such meaning-making process has been practiced as an intervention in various psychotherapies to promote wellness. Nevertheless, to support recollecting and recounting lived experiences in everyday life remains under explored in HCI. It also remains unknown how technologies such as generative AI models can facilitate the meaning making process, and ultimately support affective mindfulness. In this paper we present Metamorpheus, an affective interface that

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“…Likewise, children communicate with mechanisms by grabbing substances with their hands and using their faces. Aoki et al (2022) explored the impacts of speech balloon shapes on sender-receiver agreement concerning the emotionality of text messages. Depending on these outcomes, the author formed a system that generated speech balloons matching linear emotional arousal intensity by ACGAN.…”

Section: Journal Of Disability Research 2024mentioning

confidence: 99%

Emotion Analysis Using Improved Cat Swarm Optimization with Machine Learning for Speech-impaired People

Alshahrani,

Yaseen,

Drar

2024

Journal of Disability Research

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Emotion analysis is an effective method for improving interaction and understanding for speech-impaired people. We can provide the best interaction and support emotional well-being by analyzing the emotion conveyed through speech. Using deep learning (DL) or machine learning algorithms for training an emotion classification method. This might include training classifiers namely random forests, deep neural networks, or support vector machines. It is noteworthy that emotion analysis could be effective; however, it is crucial to consider individual differences and context while interpreting emotion. Furthermore, ensuring data protection and privacy and obtaining consent are vital features to consider while working with sensitive speech data. Therefore, this study presents an emotion analysis approach using improved cat swarm optimization with machine learning (EA-ICSOML) technique. The EA-ICSOML technique applies the concepts of computer vision and DL to identify various types of emotions. For feature vector generation, the ShuffleNet model is used in this work. To adjust the hyperparameters compared to the ShuffleNet system, the ICSO algorithm is used. Finally, the recognition and classification of emotions are performed using the Transient Chaotic Neural Network approach. The performance validation of the EA-ICSOML technique is validated on facial emotion databases. The simulation result inferred the improved emotion recognition results of the EA-ICSOML approach compared to other recent models in terms of different evaluation measures.

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EmoBalloon - Conveying Emotional Arousal in Text Chats with Speech Balloons

Cited by 22 publications

References 40 publications

Creating Emordle: Animating Word Cloud for Emotion Expression

Creating Emordle: Animating Word Cloud for Emotion Expression

Metamorpheus: Interactive, Affective, and Creative Dream Narration Through Metaphorical Visual Storytelling

Emotion Analysis Using Improved Cat Swarm Optimization with Machine Learning for Speech-impaired People

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