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

TL;DR

The paper introduces the ABCDE dataset, a large-scale, annotated collection of over 400 million text utterances from diverse sources, designed to support interdisciplinary research in affective and social sciences.

Contribution

It provides a comprehensive, annotated text dataset that addresses accessibility issues and enables research across multiple scientific disciplines.

Findings

Contains over 400 million text utterances from various sources

Annotated with a wide range of affective and social features

Facilitates interdisciplinary research in multiple fields

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.