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

Neemesh Yadav, Mohammad Aflah Khan, Diksha Sethi, Raghav Sahni

Keywords: Hope Speech, NLP, Social Good, Social Computing, Classification, HopeEDI dataset, LT-EDI-2021, LT-EDI-2022

TL;DR: We analyze submissions to the previous Hope Speech Shared Tasks and show their pitfalls while outperforming them in terms of performance or training efficiency.

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 ``YouTube comments/posts 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. Our codes for replicating our findings will be made available in the near future.

Community Implementations: [ 1 code implementation](https://www.catalyzex.com/paper/arxiv:2306.01742/code)