--- title: "Affect, Body, Cognition, Demographics, and Emotion: The" description: "To lower this barrier, the authors release ABCDE, a dataset of more than 400 million text instances. 2 references, cited by 3 papers here." authors: ["Jan Philip Wahle", "Krishnapriya Vishnubhotla", "Bela Gipp", "Saif M. Mohammad"] year: 2026 venue: "Proceedings of Computational Affective Science (CAS) @ LREC 2026" source: "https://aclanthology.org/2026.cas-1.19/" doi: "10.63317/4sy7eqwffec6" licence: "CC BY-NC 4.0 (ELRA, LREC proceedings)" licence_url: "https://creativecommons.org/licenses/by-nc/4.0/" summary_licence: "Elamur Cosmic License" canonical: "https://research.elamur.ai/free/en/papers/wahle-2026-affect-body-cognition-demographics-emotion/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/wahle-2026-affect-body-cognition-demographics-emotion/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [2026](https://md.research.elamur.ai/free/en/papers/2026/page/5/) / Affect, Body, Cognition, Demographics, and Emotion: The ABCDE of Text Features for Computational Affective Science # Affect, Body, Cognition, Demographics, and Emotion: The ABCDE of Text Features for Computational Affective Science **Authors:** [Jan Philip Wahle](https://md.research.elamur.ai/free/en/authors/jan-philip-wahle/), [Krishnapriya Vishnubhotla](https://md.research.elamur.ai/free/en/authors/krishnapriya-vishnubhotla/), [Bela Gipp](https://md.research.elamur.ai/free/en/authors/bela-gipp/) and [Saif M. Mohammad](https://md.research.elamur.ai/free/en/authors/saif-mohammad/) · **Year:** 2026 · **Venue:** [Proceedings of Computational Affective Science (CAS) @ LREC 2026](https://md.research.elamur.ai/free/en/venues/cas/) ([Computational Affective Science (CAS) @ LREC 2026](https://md.research.elamur.ai/free/en/venues/cas/2026/)) · **Publisher:** [European Language Resources Association (ELRA)](https://md.research.elamur.ai/free/en/publishers/european-language-resources-association-elra/) · **Licence:** [CC BY-NC 4.0 (ELRA, LREC proceedings)](https://creativecommons.org/licenses/by-nc/4.0/) **Links:** [Publisher's page](https://aclanthology.org/2026.cas-1.19/) · [PDF](https://aclanthology.org/2026.cas-1.19.pdf) · [DOI 10.63317/4sy7eqwffec6](https://doi.org/10.63317/4sy7eqwffec6) · [OpenAlex](https://openalex.org/W7166575922) **Citations:** 0 citations (OpenAlex, 2026-10-14) · [3](https://md.research.elamur.ai/free/en/papers/wahle-2026-affect-body-cognition-demographics-emotion/cited-by/) in our library, of the 149,439 papers whose bibliographies we read ## Summary Research in computational affective and social science often requires text that has already been tagged with features such as emotion-word usage or the author's age. The tools for producing these labels are scattered and difficult to use, especially for scholars without a computer science background. To lower this barrier, the authors release ABCDE, a dataset of more than 400 million text instances. It combines social media posts, blogs, books, and AI-generated material, including human–LLM chats, reasoning traces, preference data, and detection corpora. Each instance comes with 136 pre-computed lexical features grouped into five themes: Affect, Body, Cognition, Demographics, and Emotion. Most features are lexicon-based, for example valence/arousal/dominance, warmth/competence, body part mentions, and thinking verbs. Demographic attributes are inferred from explicit self-disclosure statements using regex patterns. Unlike toolkits such as LIWC or VADER, which only extract features, ABCDE ships the data and the annotations together. This gives researchers a standardized, reproducible starting point for population-level statistical analysis across fields such as psychology, sociology, the digital humanities, and NLP. ## Key points - **Data sources:** - Twitter (TUSC, 2015–2021): 45.2M geolocated tweets. - Reddit (Pushshift, 2010–2022): about 78.6M posts. - Google Books Ngram English Fiction (1800–2012): 177.1M 5-gram occurrences, covering 1.74M unique 5-grams. - Blogs: 34.2M instances. - AI-generated text (2022–2025): 68.9M instances. - **Reddit filtering:** posts flagged over_18, promoted posts, posts with images or videos, and posts shorter than 5 or longer than 1,000 words were removed. - **Feature set:** - Emotion and VAD scores, warmth/competence, and anxiety/calmness. - Body part mentions from a released anatomical inventory. - Cognition terms in categories such as memory, decision making, and creativity, plus tense and pronoun use. - **Demographic extraction:** self-disclosure regex patterns label age, occupation, gender, country, city, and religion, for example from statements of the form "I work as" a given occupation. - **Availability:** the dataset is at hf.co/datasets/jpwahle/abcde and the code at github.com/jpwahle/abcde. *Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.* ## Institutions - [National Research Council Canada](https://md.research.elamur.ai/free/en/government/national-research-council-canada/) — Government body, Ottawa, Canada · 59 works · 21,677 citations - [University of Göttingen](https://md.research.elamur.ai/free/en/universities/university-of-gottingen/) — University, Göttingen, Germany · 17 works · 158 citations 📚 Shelves (5): [🖥️ Computer Science](https://md.research.elamur.ai/free/en/shelves/computer-science/) · 16,667 works · [🤖 Artificial Intelligence](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · 16,194 works · [💭 Psychology](https://md.research.elamur.ai/free/en/shelves/psychology/) · 1,552 works · [💭 Experimental and Cognitive Psychology](https://md.research.elamur.ai/free/en/shelves/psychology/experimental-and-cognitive-psychology/) · 870 works · [💭 Social Psychology](https://md.research.elamur.ai/free/en/shelves/psychology/social-psychology/) · 306 works 🧭 Topics (1): [😊 Sentiment & emotion](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/) · 972 works ## Cite Cite as: Jan Philip Wahle, Krishnapriya Vishnubhotla, Bela Gipp and Saif M. Mohammad. 2026. Affect, Body, Cognition, Demographics, and Emotion: The ABCDE of Text Features for Computational Affective Science. Proceedings of Computational Affective Science (CAS) @ LREC 2026. The paper itself, not this page. BibTeX from the library's record of the work. ```bibtex @inproceedings{wahle2026affect, title = {{Affect, Body, Cognition, Demographics, and Emotion: The ABCDE of Text Features for Computational Affective Science}}, author = {Jan Philip Wahle, Krishnapriya Vishnubhotla, Bela Gipp and Saif M. Mohammad}, booktitle = {Proceedings of Computational Affective Science (CAS) @ LREC 2026}, year = {2026}, doi = {10.63317/4sy7eqwffec6}, url = {https://doi.org/10.63317/4sy7eqwffec6} } ``` - [← previous A Systematic Comparison of Parameter-Efficient Fine-Tuning Techniques for Low-Resource Neural Machine Translation: Evidence from Indigenous Languages of the Americas](https://md.research.elamur.ai/free/en/papers/stackhouse-2026-systematic-comparison-parameter-efficient-fine/) - [next → Agentic Rubrics as Contextual Verifiers for SWE Agents](https://md.research.elamur.ai/free/en/papers/raghavendra-2026-agentic-rubrics-as-contextual-verifiers/) - [↑ back to papers of 2026](https://md.research.elamur.ai/free/en/papers/2026/page/5/) ## References 2 references, 1 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet. 1. Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023. [GPT-4 technical report](https://md.research.elamur.ai/free/en/papers/openai-2023-gpt-4-technical-report/). arXiv preprint arXiv:2303.08774. 2. Mutaz Ayesh, Saif M. Mohammad, and Nedjma Ousidhoum. 2026. Annotating dimensions of social perception in text: The first sentence-level dataset of warmth and competence. [find](https://scholar.google.com/scholar?q=Mutaz+Ayesh%2C+Saif+M%2E+Mohammad%2C+and+Nedjma+Ousidhoum%2E+2026%2E+Annotating+dimensions+of+social+perception+in+text%3A+The+first+sentence%2Dlevel+dataset+of+warmth+and+competence%2E) *Updated 1 November 2026*