Echoes of Discord: Forecasting Hater Reactions to Counterspeech

TL;DR

The paper addresses how haters react to counterspeech in online discussions by introducing the ReEco dataset of Reddit HS–counterspeech triples with labeled hater reentry. It investigates two predictive approaches—a two-stage predictor and a 3-way classifier—finding that the 3-way model most accurately forecasts outcomes, while LLMs underperform compared to BERT-based architectures. Through linguistic analysis, it identifies signals in counterspeech that influence reentry and reentry type, highlighting the role of emotional tone and social cues. These insights advance counterspeech design and evaluation, offering practical implications for reducing further hatful engagement on platforms, though the study is limited to immediate, triple-turn interactions and calls for broader context and long-term analyses.

Abstract

Hate speech (HS) erodes the inclusiveness of online users and propagates negativity and division. Counterspeech has been recognized as a way to mitigate the harmful consequences. While some research has investigated the impact of user-generated counterspeech on social media platforms, few have examined and modeled haters' reactions toward counterspeech, despite the immediate alteration of haters' attitudes being an important aspect of counterspeech. This study fills the gap by analyzing the impact of counterspeech from the hater's perspective, focusing on whether the counterspeech leads the hater to reenter the conversation and if the reentry is hateful. We compile the Reddit Echoes of Hate dataset (ReEco), which consists of triple-turn conversations featuring haters' reactions, to assess the impact of counterspeech. To predict haters' behaviors, we employ two strategies: a two-stage reaction predictor and a three-way classifier. The linguistic analysis sheds insights on the language of counterspeech to hate eliciting different haters' reactions. Experimental results demonstrate that the 3-way classification model outperforms the two-stage reaction predictor, which first predicts reentry and then determines the reentry type. We conclude the study with an assessment showing the most common errors identified by the best-performing model.

Figures (1)

• Figure 1: Hater's non-hateful reentry as a conversation outcome. A Reddit user (hater) posts HS. Another user, $U_{1}$, replies with countersppech. This is followed by subsequent replies ($R_{1}$, $R_{2}$, ...$R_{j}$). The counterspeech prompts the hater to reenter the conversation with a non-hateful post. Grey boxes represent HS.