Abstract
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.
Highlights
Theoretical frameworks for figurative language posit eight standard forms: indirect questions, idiom, irony and sarcasm, metaphor, simile, hyperbole, understatement, and rhetorical questions (a) Rhetorical questions (RQs) in Forums Dialog (b) RQs in Twitter Dialog (Roberts and Kreuz, 1994)
We show that we can distinguish between SARCASTIC and OTHER uses of RQs that we observe, such as argumentation and persuasion in forums and Twitter, respectively
We present experiments classifying rhetorical vs. information-seeking questions, sarcastic vs. other uses of RQs
Summary
Theoretical frameworks for figurative language posit eight standard forms: indirect questions, idiom, irony and sarcasm, metaphor, simile, hyperbole, understatement, and rhetorical questions. C 2017 Association for Computational Linguistics some forms of figurative language have been facilitated by the use of hashtags in Twitter, e.g. the #sarcasm hashtag (Bamman and Smith, 2015; Riloff et al, 2013; Liebrecht et al, 2013). Other figurative forms, such as similes, can be identified via lexico-syntactic patterns (Qadir et al, 2016, 2015; Veale and Hao, 2007). We present a novel task, dataset, and results aimed at understanding how RQs can be recognized, and how sarcastic and other uses of RQs can be distinguished
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