分析政治播客对话链，发现毒性语言会随回复递增
Toxicity Begets Toxicity: Unraveling Conversational Chains in Political Podcasts
- 构建政治播客对话数据集，研究回复序列中的毒性演化
- 发现对话中负面言论常在连续回复中逐轮升级
- 适合关注网络言辞演化与内容安全的研究者
数字通信中的毒性行为仍是学界与业界的紧迫议题。尽管社交平台和讨论区的毒性研究已较充分，但随着播客迅速走红，其相关研究仍相对匮乏。本文通过构建政治播客转录文本数据集，聚焦对话结构，分析毒性如何在连续回复序列中浮现并加剧，揭示有害语言在对话轮次间自然演化的模式。警告：内容可能包含侮辱性或有毒言论。
原文摘要 · Abstract (English)
Tackling toxic behavior in digital communication continues to be a pressing concern for both academics and industry professionals. While significant research has explored toxicity on platforms like social networks and discussion boards, podcasts despite their rapid rise in popularity remain relatively understudied in this context. This work seeks to fill that gap by curating a dataset of political podcast transcripts and analyzing them with a focus on conversational structure. Specifically, we investigate how toxicity surfaces and intensifies through sequences of replies within these dialogues, shedding light on the organic patterns by which harmful language can escalate across conversational turns. Warning: Contains potentially abusive/toxic contents.
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