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Lowri Williams, Eirini Anthi and Pete Burnap
The performance of emotive text classification using affective hierarchical schemes (e.g., WordNet-Affect) is often evaluated using the same traditional measures used to evaluate the performance of when a finite set of isolated classes are used. However,...
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Peranut Nimitsurachat and Peter Washington
Emotion recognition models using audio input data can enable the development of interactive systems with applications in mental healthcare, marketing, gaming, and social media analysis. While the field of affective computing using audio data is rich, a m...
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Moritz Müller, Ambre Dupuis, Tobias Zeulner, Ignacio Vazquez, Johann Hagerer and Peter A. Gloor
Well-being is one of the pillars of positive psychology, which is known to have positive effects not only on the personal and professional lives of individuals but also on teams and organizations. Understanding and promoting individual well-being is esse...
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Yao Qin, Yiping Shi, Xinze Hao and Jin Liu
Microblog is an important platform for mining public opinion, and it is of great value to conduct emotional analysis of microblog texts during the current epidemic. Aiming at the problem that most current emotional classification methods cannot effective...
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Sakib Shahriar, Noora Al Roken and Imran Zualkernan
The automatic classification of poems into various categories, such as by author or era, is an interesting problem. However, most current work categorizing Arabic poems into eras or emotions has utilized traditional feature engineering and machine learni...
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Omar Adel, Karma M. Fathalla and Ahmed Abo ElFarag
Emotion recognition is crucial in artificial intelligence, particularly in the domain of human?computer interaction. The ability to accurately discern and interpret emotions plays a critical role in helping machines to effectively decipher users? underly...
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Lihong Zhang, Chaolong Liu and Nan Jia
Multimodal emotion classification (MEC) has been extensively studied in human?computer interaction, healthcare, and other domains. Previous MEC research has utilized identical multimodal annotations (IMAs) to train unimodal models, hindering the learning...
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Oleg Kalyta, Olexander Barmak, Pavlo Radiuk and Iurii Krak
Can be used in video surveillance systems for large groups of people.
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Charalampos M. Liapis and Sotiris Kotsiantis
The use of deep learning in conjunction with models that extract emotion-related information from texts to predict financial time series is based on the assumption that what is said about a stock is correlated with the way that stock fluctuates. Given th...
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Zhipeng Zhang and Liyi Zhang
Electroencephalography (EEG)-based emotion recognition technologies can effectively help robots to perceive human behavior, which have attracted extensive attention in human?machine interaction (HMI). Due to the complexity of EEG data, current researcher...
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