To ensure consistent and informed performances while preserving natural interpretative variation, participants received comprehensive preparation materials before their recording sessions.

Key components of the instructions:

• Humour Style Definitions: Clear explanations of affiliative, self-enhancing, aggressive, self-deprecating, and neutral categories

• Emotion Guidelines : Six emotional categories (joy, empathy, anger, neutral, embarrassment, superiority) for varied interpretations

• Preparation Protocol: Guidance on familiarizing with content, practicing delivery variations, and considering facial expressions

• Ethical Considerations: Important note about potentially offensive content included for research purposes only

• Recording Day Expectations: Overview of the 2.5-hour session structure and emotion reporting process

The instructions emphasised that "there are no 'correct' interpretations" - encouraging participants' natural portrayal across different emotional spectrums while maintaining understanding of each humour style's psychological foundation.

📥 Download Full Participant Instructions (PDF)

🔗 File Naming Convention 

• {participant_id}_{performance_type}_{actor_type}_{humor_style}_{joke_id}.mp4  

Where:  

• participant_id: p01, p02, ..., p50 

• performance_type: orig (original) | rep2/rep3/rep4 (re-performance) 

• actor_type: same (same actor) | diff (different actor) 

• humour_style: selfenh | selfdep | affil | aggr | neutral 

• joke_id: or001, or002, ..., or1463 

Examples:

• p01_orig_selfenh_or109.mp4 (original performance)

• p12_rep2_diff_aggr_or677.mp4 (re-performance by different actor)

• p25_rep2_same_neutral_or432.mp4 (re-performance by same actor)

🧠 Psychological Research

🎙️ Conversational Agents

🔍 Content Moderation Tools

📱 Mental Wellness Apps

🏥 Clinical Assessment

🏢 Workplace Communication Training 

If you use the MultiHuSE dataset, please cite: 

Kenneth, O. M., Khosmood, F., & Edalat, A. (2025). MultiHuSE: A Multimodal Dataset for Humour Styles and Emotions. In Proceedings of the IEEE International Conference on Multimedia Indexing (CBMI 2025), Dublin, Ireland. (Accepted). 

BibTex:

@inproceedings{kenneth2025multihuse,

  author    = {Kenneth, O. Mary and Khosmood, Foaad and Edalat, Abbas},

  title     = {MultiHuSE: A Multimodal Dataset for Humour Styles and Emotions},

  booktitle = {Proceedings of the IEEE International Conference on Multimedia Indexing (CBMI 2025)},

  year      = {2025},

  address   = {Dublin, Ireland},

  note      = {(Accepted)}

}

Related Work:

• Kenneth, O. Mary, Khosmood, Foaad and Edalat, Abbas (2025). “Explaining Humour Style Classifications: An XAI Approach to Understanding Computational Humour Analysis” in Journal of Data Mining and Digital Humanities. https://arxiv.org/abs/2501.02891

• Kenneth, O. Mary, Khosmood, Foaad and Edalat, Abbas (2024). "A Two-Model Approach for Humour Style Recognition ". In Proceedings of the  4th International Conference on Natural Language Processing for Digital Humanities, pages 259–274, Miami, USA. Association for Computational Linguistics. doi: https://doi.org/10.18653/v1/2024.nlp4dh-1.25 

• Kenneth, O. Mary, Khosmood, Foaad and Edalat, Abbas (2024). “Systematic Literature Review: Computational Approaches for Humour Style Classification” in arXiv. doi: https://doi.org/10.48550/arXiv.2402.01759

For access questions, dataset collaborations, or feedback, contact:

• 📧 Mary Ogbuka Kenneth: m.kenneth22@imperial.ac.uk 

• Algorithmic Human Development Group, Imperial College London.

Dataset created with ethics approval from Imperial College London SETREC