# Hope Speech Detection: A Computational Analysis of the Voice of Peace

arXiv: https://arxiv.org/abs/1909.12940 · HTML: https://mlsanity.com/paper/1909.12940/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Sep 2019.

## Built on by (most cited first, 15 of 15)

- [CounterGeDi: A controllable approach to generate polite, detoxified and emotional counterspeech](https://mlsanity.com/paper/2205.04304/) (2022)
- [NLP for Counterspeech against Hate: A Survey and How-To Guide](https://mlsanity.com/paper/2403.20103/) (2024)
- [PolyHope: Two-Level Hope Speech Detection from Tweets](https://mlsanity.com/paper/2210.14136/) (2022)
- [Hope Speech detection in under-resourced Kannada language](https://mlsanity.com/paper/2108.04616/) (2021)
- [IIITT@LT-EDI-EACL2021-Hope Speech Detection: There is always Hope in Transformers](https://mlsanity.com/paper/2104.09066/) (2021)
- [Northeastern Uni at Multilingual Counterspeech Generation: Enhancing Counter Speech Generation with LLM Alignment through Direct Preference Optimization](https://mlsanity.com/paper/2412.15453/) (2024)
- [Social Support Detection from Social Media Texts](https://mlsanity.com/paper/2411.02580/) (2024)
- [End-to-End Natural Language Understanding Pipeline for Bangla Conversational Agents](https://mlsanity.com/paper/2107.05541/) (2021)
- [Hope vs. Hate: Understanding User Interactions with LGBTQ+ News Content in Mainstream US News Media through the Lens of Hope Speech](https://mlsanity.com/paper/2502.09004/) (2025)
- [Optimism, Expectation, or Sarcasm? Multi-Class Hope Speech Detection in Spanish and English](https://mlsanity.com/paper/2504.17974/) (2025)
- [Hopeful_Men@LT-EDI-EACL2021: Hope Speech Detection Using Indic Transliteration and Transformers](https://mlsanity.com/paper/2102.12082/) (2021)
- [Understanding peacefulness through the world news](https://mlsanity.com/paper/2106.00306/) (2021)
- [Community Learning: Understanding A Community Through NLP for Positive Impact](https://mlsanity.com/paper/2210.00590/) (2022)
- [Beyond Negativity: Re-Analysis and Follow-Up Experiments on Hope Speech Detection](https://mlsanity.com/paper/2306.01742/) (2023)
- [GHaLIB: A Multilingual Framework for Hope Speech Detection in Low-Resource Languages](https://mlsanity.com/paper/2512.22705/) (2025)

## Abstract (arXiv)

The recent Pulwama terror attack (February 14, 2019, Pulwama, Kashmir) triggered a chain of escalating events between India and Pakistan adding another episode to their 70-year-old dispute over Kashmir. The present era of ubiquitious social media has never seen nuclear powers closer to war. In this paper, we analyze this evolving international crisis via a substantial corpus constructed using comments on YouTube videos (921,235 English comments posted by 392,460 users out of 2.04 million overall comments by 791,289 users on 2,890 videos). Our main contributions in the paper are three-fold. First, we present an observation that polyglot word-embeddings reveal precise and accurate language clusters, and subsequently construct a document language-identification technique with negligible annotation requirements. We demonstrate the viability and utility across a variety of data sets involving several low-resource languages. Second, we present an analysis on temporal trends of pro-peace and pro-war intent observing that when tensions between the two nations were at their peak, pro-peace intent in the corpus was at its highest point. Finally, in the context of heated discussions in a politically tense situation where two nations are at the brink of a full-fledged war, we argue the importance of automatic identification of user-generated web content that can diffuse hostility and address this prediction task, dubbed hope-speech detection.