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This repository is created to support the paper 'CAMS: An Annotated Corpus for Causal Analysis of Mental health on Social media' which is submitted to Language Resources and Evaluation Conference 2022 we introduce a new dataset for Causal Analysis of Mental health illness in Social media posts (CAMS). We first introduce the annotation schema for this task of causal analysis. The causal analysis comprises two types of annotations, viz, causal interpretation and causal categorization. We show the efficacy of our scheme in two ways: (i) crawling and annotating 3155 Reddit data and (ii) re-annotate the publicly available SDCNL dataset of 1896 instances for interpretable causal analysis. We further combine them as CAMS dataset.

Python 5.54% Jupyter Notebook 94.46%

cams's Introduction

CAMS

An Annotated Corpus for Causal Analysis of Mental Health Issues in Social Media Posts

This repository is created to support the paper 'CAMS: An Annotated Corpus for Causal Analysis of Mental health on Social media' (accepted (published) in Language Resources and Evaluation Conference LREC'2022)

We introduce a new dataset for Causal Analysis of Mental health illness in Social media posts (CAMS). We first introduce the annotation schema for this task of causal analysis. The causal analysis comprises two types of annotations, viz, causal interpretation and causal categorization. We show the efficacy of our scheme in two ways: (i) crawling and annotating 3155 Reddit data and (ii) re-annotate the publicly available SDCNL dataset of 1896 instances for interpretable causal analysis. We further combine them as CAMS dataset.

Dataset Overview

The labeled data could be downloaded from here.

Terms of use

  • This corpus can be used freely for research purposes.
  • The paper provides details of the creation and use of the corpus.
  • If you use the corpus, then please cite the paper.
  • Please feel free to send us an email:
    • with feedback regarding the corpus.
    • with information on how you have used the corpus.
    • if interested in a collaborative research project.

cams's People

Contributors

cmooncs avatar drmuskangarg avatar prateekmittal154 avatar

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