Beyond Negativity: Re-Analysis and Follow-Up Experiments on Hope Speech Detection

Neemesh Yadav, Mohammad Aflah Khan, Diksha Sethi, Raghav Sahni
5/10/2023
cs.CLcs.LG

Official code: aflah02/Hope_Speech_Detection (5 stars, last commit 2023-11-11).

Abstract

Health experts assert that hope plays a crucial role in enhancing individuals' physical and mental well-being, facilitating their recovery, and promoting restoration. Hope speech refers to comments, posts and other social media messages that offer support, reassurance, suggestions, inspiration, and insight. The detection of hope speech involves the analysis of such textual content, with the aim of identifying messages that invoke positive emotions in people. Our study aims to find computationally efficient yet comparable/superior methods for hope speech detection. We also make our codebase public at https://github.com/aflah02/Hope_Speech_Detection

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Code Implementations(1)

aflah02/Hope_Speech_DetectionOfficial100%

Hope Speech Detection (Shared Task from Workshop on Language Technology For Equality, Diversity, Inclusion Shared Task (LT-EDI) in 2021 and 2022) using Machine Learning & Deep Learning

50Python, Jupyter NotebookSep 12, 20222 years ago
classificationhope-speechmlnlp

Cite this paper

@article{yadav2023beyond,
  title  = {Beyond Negativity: Re-Analysis and Follow-Up Experiments on Hope Speech Detection},
  author = {Neemesh Yadav and Mohammad Aflah Khan and Diksha Sethi and Raghav Sahni},
  year   = {2023},
  eprint = {2306.01742},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2306.01742v1}
}

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