Determining Relative Argument Specificity and Stance for Complex Argumentative Structures

39517

Authors

nan

Abstract

AbstractSystems for automatic argument generation and debate require the ability to (1) determine the stance of any claims employed in the argument and (2) assess the specificity of each claim relative to the argument context. Existing work on understanding claim specificity and stance, however, has been limited to the study of argumentative structures that are relatively shallow, most often consisting of a single claim that directly supports or opposes the argument thesis. In this paper, we tackle these tasks in the context of complex arguments on a diverse set of topics. In particular, our dataset consists of manually curated argument trees for 741 controversial topics covering 95,312 unique claims; lines of argument are generally of depth 2 to 6. We find that as the distance between a pair of claims increases along the argument path, determining the relative specificity of a pair of claims becomes easier and determining their relative stance becomes harder.

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Full Content

Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 4630–4641 Florence, Italy, July 28 - August 2, 2019. c⃝2019 Association for Computational Linguistics 4630 Determining Relative Argument Specificity and Stance for Complex Argumentative Structures Esin Durmus Cornell University ed459@cornell.edu Faisal Ladhak Amazon faisall@amazon.com Claire Cardie Cornell University cardie@cs.cornell.edu Abstract Systems for automatic argument generation and debate require the ability to (1) determine the stance of any claims employed in the ar- gument and (2) assess the specificity of each claim relative to the argument context. Ex- isting work on understanding claim specificity and stance, however, has been limited to the study of argumentative structures that are rel- atively shallow, most often consisting of a sin- gle claim that directly supports or opposes the argument thesis. In this paper, we tackle these tasks in the context of complex arguments on a diverse set of topics. In particular, our dataset consists of manually curated argument trees for 741 controversial topics covering 95,312 unique claims; lines of argument are gener- ally of depth 2 to 6. We find that as the dis- tance between a pair of claims increases along the argument path, determining the relative specificity of a pair of claims becomes easier and determining their relative stance becomes harder. 1 Introduction The tasks of automatic argument generation and debate require the ability to present a diverse and comprehensive set of supporting and opposing ar- guments given a controversial topic. Two criti- cal components of such systems are an ability to determine the stance and the specificity of any claims employed in the proposed argument. Con- sider, for example, the argument thesis (i.e., the topic) of Figure 1: (THESIS) Would we like to live in the world of Harry Potter? Construction of an argument in support or in opposition to this the- sis necessarily requires knowing the stance of the claims that comprise it: the claim Magic opens a lot of interesting possibilities should be identified as a claim in support of the THESIS, and The ca- pacity of harm is greater when magic is involved (HARM), as a claim in opposition. Indeed, pre- vious work has studied this task (e.g., Bar-Haim et al. (2017); Faulkner (2014)). It is not sufficient, however, to determine claim stance only with respect to the argument thesis. Debate and argument generation systems, in gen- eral, should also be able to determine whether two claims that address the same line of reasoning rep- resent the same, or the opposing stance: using De- fense is also made easier through magic to refute the HARM claim in Figure 1, for example, requires recognizing that it represents the opposite stance. The issue of claim specificity in argumentation has been much less addressed. Existing work, however, suggests that a high degree of speci- ficity is correlated with argument quality and per- suasiveness (Carlile et al., 2018; Swanson et al., 2015). In terms of argument quality though, it is entirely possible for the presented claims to be co- …

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Labeled Text

AbstractSystems for automatic argument generation and debate require the ability to (1) determine the stance of any claims employed in the argument and (2) assess the specificity of each claim relative to the argument context. Existing work on understanding claim specificity and stance, however, has been limited to the study of argumentative structures that are relatively shallow, most often consisting of a single claim that directly supports or opposes the argument thesis. In this paper, we tackle these tasks in the context of complex arguments on a diverse set of topics. In particular, our dataset consists of manually curated argument trees for 741 controversial topics covering 95,312 unique claims; lines of argument are generally of depth 2 to 6. We find that as the distance between a pair of claims increases along the argument path, determining the relative specificity of a pair of claims becomes easier and determining their relative stance becomes harder.

Publication Details

Paper ID:
39517
Year:
2019
Publication:
TIPSTER
Publication Type:
conf
DOI:
nan