Affect, Body, Cognition, Demographics, and Emotion: The ABCDE of Text Features for Computational Affective Science
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866918424602476544 |
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| author | Wahle, Jan Philip Vishnubhotla, Krishnapriya Gipp, Bela Mohammad, Saif M. |
| author_facet | Wahle, Jan Philip Vishnubhotla, Krishnapriya Gipp, Bela Mohammad, Saif M. |
| contents | Work in Computational Affective Science and Computational Social Science explores a wide variety of research questions about people, emotions, behavior, and health. Such work often relies on language data that is first labeled with relevant information, such as the use of emotion words or the age of the speaker. Although many resources and algorithms exist to enable this type of labeling, discovering, accessing, and using them remains a substantial impediment, particularly for practitioners outside of computer science. Here, we present the ABCDE dataset (Affect, Body, Cognition, Demographics, and Emotion), a large-scale collection of over 400 million text utterances drawn from social media, blogs, books, and AI-generated sources. The dataset is annotated with a wide range of features relevant to computational affective and social science. ABCDE facilitates interdisciplinary research across numerous fields, including affective science, cognitive science, the digital humanities, sociology, political science, and computational linguistics. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_17752 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Affect, Body, Cognition, Demographics, and Emotion: The ABCDE of Text Features for Computational Affective Science Wahle, Jan Philip Vishnubhotla, Krishnapriya Gipp, Bela Mohammad, Saif M. Computation and Language Work in Computational Affective Science and Computational Social Science explores a wide variety of research questions about people, emotions, behavior, and health. Such work often relies on language data that is first labeled with relevant information, such as the use of emotion words or the age of the speaker. Although many resources and algorithms exist to enable this type of labeling, discovering, accessing, and using them remains a substantial impediment, particularly for practitioners outside of computer science. Here, we present the ABCDE dataset (Affect, Body, Cognition, Demographics, and Emotion), a large-scale collection of over 400 million text utterances drawn from social media, blogs, books, and AI-generated sources. The dataset is annotated with a wide range of features relevant to computational affective and social science. ABCDE facilitates interdisciplinary research across numerous fields, including affective science, cognitive science, the digital humanities, sociology, political science, and computational linguistics. |
| title | Affect, Body, Cognition, Demographics, and Emotion: The ABCDE of Text Features for Computational Affective Science |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2512.17752 |