Disagreements are frequently studied from the perspective of either detecting toxicity or analysing argument structure. We propose a framework of dispute tactics that unifies these two perspectives, as well as other dialogue acts which play a role in resolving disputes, such as asking questions and providing clarification. This framework includes a preferential ordering among rebuttal-type tactics, ranging from ad hominem attacks to refuting the central argument. Using this framework, we annotate 213 disagreements (3,865 utterances) from Wikipedia Talk pages. This allows us to investigate research questions around the tactics used in disagreements; for instance, we provide empirical validation of the approach to disagreement recommended by Wikipedia. We develop models for multilabel prediction of dispute tactics in an utterance, achieving the best performance with a transformer-based label powerset model. Adding an auxiliary task to incorporate the ordering of rebuttal tactics further yields a statistically significant increase. Finally, we show that these annotations can be used to provide useful additional signals to improve performance on the task of predicting escalation.
翻译:经常从发现毒性或分析争论结构的角度来研究分歧。 我们提出一个争议策略框架,将这两种观点以及其他对话行动统一起来,在解决争端方面发挥作用,例如提问和澄清。这个框架包括辩驳类策略的优选顺序,从人身攻击到反驳中心论点。我们利用这个框架,对维基百科Talk网页上的213个分歧(3 865个发声)进行批注。这使我们能够调查围绕分歧策略的研究问题;例如,我们对维基百科建议的分歧处理方法提供实证验证。我们开发了多标签多标签预测争议策略的模式,用变压器标签功能模型取得最佳性能。加上一个辅助任务,将反驳策略的订单纳入其中,将进一步产生统计上的重大增加。最后,我们表明,这些说明可以用来提供有用的补充信号,以改进预测升级任务的业绩。