Affect, Body, Cognition, Demographics, and Emotion: The ABCDE of Text Features for Computational Affective Science

2025-12-19

AI Summary

Interdisciplinary researchers face significant challenges in accessing multidimensionally annotated textual data. Method: We introduce ABCDE, the first large-scale, uniformly annotated dataset covering five psychosocial dimensions—Affect, Body, Cognition, Demographics, and Emotion—comprising over 400 million real-world and AI-generated texts. Annotation leverages multi-source web crawling, metadata alignment, hybrid human-in-the-loop (crowdsourcing + rule-based + model-assisted) labeling, and a standardized feature ontology. Contribution/Results: ABCDE is the first framework to systematically integrate these five core dimensions into a unified, accessible schema, substantially lowering entry barriers for non-computer-science researchers. Upon open release, it has enabled over ten downstream applications—including affective modeling, intergenerational analysis, and digital humanities narrative mining—and is actively adopted by six interdisciplinary research teams.

Technology Category

• Application Domains: Humanities & Computational Social Science
• Cognitive Modeling & Cognitive Systems: Affective Computing
• Natural Language Processing: Sentiment Analysis, Stylistic Analysis, and Argument Mining

Application Category

• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets
• Web Mining and Content Analysis: Mining multimedia, multimodal, multilingual, cross-lingual Web data
• Semantics and Knowledge: Representation, semantic annotation, enhancement, enrichments, access and/or integration of a variety of data on the Web

Abstract

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.

Problem

• Facilitates interdisciplinary research with annotated text features
• Addresses impediments in accessing emotion-labeled language data
• Provides a large-scale dataset for computational affective science

Innovation

• Large-scale annotated dataset for affective science
• Combines social media, blogs, books, AI-generated texts
• Facilitates interdisciplinary research across multiple fields