Perspective Chapter: Embracing the Complexity of Human Emotion
In this chapter, we delve into the multifaceted world of human emotions through the lens of advanced analysis techniques, aiming to unlock a deeper understanding of human behavior and decision-making processes in our digital landscape. We begin by illustrating the complexity of human emotions and th...
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| Formato: | Capítulo de libro |
| Lenguaje: | inglés |
| Publicado: |
IntechOpen
2024
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| Acceso en línea: | https://www.intechopen.com/chapters/88021 |
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| _version_ | 1879164823899471872 |
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| author | Thabit, Saeed Albarhami |
| author_browse | Thabit, Saeed Albarhami |
| author_facet | Thabit, Saeed Albarhami |
| author_sort | Thabit, Saeed Albarhami |
| building | IntechOpen |
| collection | Acceso abierto |
| description | In this chapter, we delve into the multifaceted world of human emotions through the lens of advanced analysis techniques, aiming to unlock a deeper understanding of human behavior and decision-making processes in our digital landscape. We begin by illustrating the complexity of human emotions and the significance of accurate emotion detection across various applications, from marketing and customer relationship management to healthcare and social media monitoring. This context leads us to discuss state-of-the-art emotion detection methods, including transformer-based models, context-aware emotion detection, physiological signal recognition, and multimodal emotion analysis. Here, we adopt a systematic approach to emotion analysis, utilizing the transformer-based architecture fine-tuned on a tweets dataset. Our methodology achieves an accuracy of 82.53%, a precision of 82.79%, a recall of 82.53%, and an F1 score of 82.29% in predicting emotional categories. The chapter also scrutinizes challenges, limitations, and ethical considerations in this field, including ambiguity, subjectivity, and cross-cultural variations. Finally, we glance into the future of emotion analysis, focusing on integrating emotional intelligence into artificial intelligence systems and developing personalized techniques. We aim to spur further research and collaboration in this field, thus enriching our understanding of the dynamic role of human emotions in our interconnected world. |
| doi_str_mv | 10.5772/intechopen.112701 |
| first_indexed | 2026-10-15T21:40:28Z |
| format | Book Chapter |
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<dc:title>Perspective Chapter: Embracing the Complexity of Human Emotion</dc:title>
<dc:creator>Saeed Albarhami Thabit</dc:creator>
<dc:subject>Physical Sciences, Engineering and Technology</dc:subject>
<dc:description>In this chapter, we delve into the multifaceted world of human emotions through the lens of advanced analysis techniques, aiming to unlock a deeper understanding of human behavior and decision-making processes in our digital landscape. We begin by illustrating the complexity of human emotions and the significance of accurate emotion detection across various applications, from marketing and customer relationship management to healthcare and social media monitoring. This context leads us to discuss state-of-the-art emotion detection methods, including transformer-based models, context-aware emotion detection, physiological signal recognition, and multimodal emotion analysis. Here, we adopt a systematic approach to emotion analysis, utilizing the transformer-based architecture fine-tuned on a tweets dataset. Our methodology achieves an accuracy of 82.53%, a precision of 82.79%, a recall of 82.53%, and an F1 score of 82.29% in predicting emotional categories. The chapter also scrutinizes challenges, limitations, and ethical considerations in this field, including ambiguity, subjectivity, and cross-cultural variations. Finally, we glance into the future of emotion analysis, focusing on integrating emotional intelligence into artificial intelligence systems and developing personalized techniques. We aim to spur further research and collaboration in this field, thus enriching our understanding of the dynamic role of human emotions in our interconnected world.</dc:description>
<dc:publisher>IntechOpen</dc:publisher>
<dc:date>2024-01-10</dc:date>
<dc:type>Chapter, Part Of Book</dc:type>
<dc:identifier>https://www.intechopen.com/chapters/88021</dc:identifier>
<dc:identifier>doi:10.5772/intechopen.112701</dc:identifier>
<dc:language>en</dc:language>
<dc:relation>ISBN:978-0-85014-060-6</dc:relation>
<dc:rights>https://creativecommons.org/licenses/by/3.0/</dc:rights>
<dc:source>https://www.intechopen.com/books/13148 ; Advances in Sentiment Analysis - Techniques, Applications, and Challenges</dc:source>
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| id | intech-88021 |
| institution | IntechOpen |
| isbn | 978-0-85014-060-6 |
| language | English |
| last_indexed | 2026-10-15T21:40:28Z |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | IntechOpen |
| publisherStr | IntechOpen |
| record_format | oai_dc |
| spelling | intech-880212024-01-10 Perspective Chapter: Embracing the Complexity of Human Emotion Saeed Albarhami Thabit Physical Sciences, Engineering and Technology In this chapter, we delve into the multifaceted world of human emotions through the lens of advanced analysis techniques, aiming to unlock a deeper understanding of human behavior and decision-making processes in our digital landscape. We begin by illustrating the complexity of human emotions and the significance of accurate emotion detection across various applications, from marketing and customer relationship management to healthcare and social media monitoring. This context leads us to discuss state-of-the-art emotion detection methods, including transformer-based models, context-aware emotion detection, physiological signal recognition, and multimodal emotion analysis. Here, we adopt a systematic approach to emotion analysis, utilizing the transformer-based architecture fine-tuned on a tweets dataset. Our methodology achieves an accuracy of 82.53%, a precision of 82.79%, a recall of 82.53%, and an F1 score of 82.29% in predicting emotional categories. The chapter also scrutinizes challenges, limitations, and ethical considerations in this field, including ambiguity, subjectivity, and cross-cultural variations. Finally, we glance into the future of emotion analysis, focusing on integrating emotional intelligence into artificial intelligence systems and developing personalized techniques. We aim to spur further research and collaboration in this field, thus enriching our understanding of the dynamic role of human emotions in our interconnected world. IntechOpen 2024-01-10 Chapter, Part Of Book https://www.intechopen.com/chapters/88021 doi:10.5772/intechopen.112701 en ISBN:978-0-85014-060-6 https://creativecommons.org/licenses/by/3.0/ https://www.intechopen.com/books/13148 ; Advances in Sentiment Analysis - Techniques, Applications, and Challenges |
| spellingShingle | Physical Sciences, Engineering and Technology Thabit, Saeed Albarhami Perspective Chapter: Embracing the Complexity of Human Emotion |
| title | Perspective Chapter: Embracing the Complexity of Human Emotion |
| title_full | Perspective Chapter: Embracing the Complexity of Human Emotion |
| title_fullStr | Perspective Chapter: Embracing the Complexity of Human Emotion |
| title_full_unstemmed | Perspective Chapter: Embracing the Complexity of Human Emotion |
| title_short | Perspective Chapter: Embracing the Complexity of Human Emotion |
| title_sort | perspective chapter embracing the complexity of human emotion |
| topic | Physical Sciences, Engineering and Technology |
| url | https://www.intechopen.com/chapters/88021 |
| work_keys_str_mv | AT thabitsaeedalbarhami perspectivechapterembracingthecomplexityofhumanemotion |