AxiOM & M3H: Figurative and Commonsense Mental Health Meme Classification

This repository contains the AxiOM and RESTORE datasets along with the implementation of the M3H framework, as proposed in our WWW’25 paper:

📄 Paper: Figurative-cum-Commonsense Knowledge Infusion for Multimodal Mental Health Meme Classification
📅 Conference: The Web Conference (WWW), 2025

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To get the access to the M3H Dataset, kindly fill the google form given below:

Google Form: https://forms.gle/9hGoVRLzuHXJyVrN6

📊 Dataset Statistics

🧠 AxiOM (Anxiety Meme Dataset)

• Total memes: 3,582
• Task: Multiclass classification
• Label categories (based on GAD-7 symptoms):
  • NV: Nervousness
  • LWC: Lack of Worry Control
  • EW: Excessive Worry
  • DR: Difficulty Relaxing
  • RST: Restlessness
  • ID: Impending Doom

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🧩 RESTORE (Depression Meme Dataset)

• Total memes: 7,396
• Task: Multilabel classification
• Label categories (based on PHQ-9, excluding "Lack of Energy"):
  • LOI: Lack of Interest
  • FD: Feeling Down
  • ED: Eating Disorder
  • SD: Sleeping Disorder
  • CP: Concentration Problem
  • LSE: Low Self-Esteem
  • SH: Self-Harm

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If you use the Our dataset, please cite:

Axiom Dataset Citation (Anxiety)

@article{mazhar2025figurative,
  title={Figurative-cum-Commonsense Knowledge Infusion for Multimodal Mental Health Meme Classification},
  author={Mazhar, Abdullah and Srivastava, Aseem and Ruhnke, Polly and Vaddavalli, Lavanya and Katragadda, Sri Keshav and Yadav, Shweta and Akhtar, Md Shad and others},
  journal={arXiv preprint arXiv:2501.15321},
  year={2025}
}

Restore Dataset Citation (Depressive)

@inproceedings{yadav2023towards,
  title={Towards identifying fine-grained depression symptoms from memes},
  author={Yadav, Shweta and Caragea, Cornelia and Zhao, Chenye and Kumari, Naincy and Solberg, Marvin and Sharma, Tanmay},
  booktitle={Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  pages={8890--8905},
  year={2023}
}