Effective models of social dialog must understand a broad range of rhetorical
and figurative devices. Rhetorical questions (RQs) are a type of figurative
language whose aim is to achieve a pragmatic goal, such as structuring an
argument, being persuasive, emphasizing a point, or being ironic. While there
are computational models for other forms of figurative language, rhetorical
questions have received little attention to date. We expand a small dataset
from previous work, presenting a corpus of 10,270 RQs from debate forums and
Twitter that represent different discourse functions. We show that we can
clearly distinguish between RQs and sincere questions (0.76 F1). We then show
that RQs can be used both sarcastically and non-sarcastically, observing that
non-sarcastic (other) uses of RQs are frequently argumentative in forums, and
persuasive in tweets. We present experiments to distinguish between these uses
of RQs using SVM and LSTM models that represent linguistic features and
post-level context, achieving results as high as 0.76 F1 for "sarcastic" and
0.77 F1 for "other" in forums, and 0.83 F1 for both "sarcastic" and "other" in
tweets. We supplement our quantitative experiments with an in-depth
characterization of the linguistic variation in RQs.

本文绘制了一系列修辞问题 (RQs)，阐述其在不同的语境中的论点阐述作用和说服作用，通过 SVM 和 LSTM 对 RQs 结构和上下文进行建模，成功地将其分为讽刺和其他两种类型，在推特中达到 0.83 的 F1 值的预测准确率，同时进行了深入的关于 RQs 的语言学变化的表征。