Modeling Argument Strength in Student Essays

Persing, Isaac; Ng, Vincent

doi:10.3115/v1/p15-1053

Cited by 120 publications

(111 citation statements)

References 16 publications

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“…For instance, Feng and Hirst (2011) classify the inference scheme of arguments based on the model of Walton et al (2008). Persing and Ng (2015) score the argument strength of persuasive essays, and Habernal and Gurevych (2016) predict which of a pair of arguments is more convincing. Such approaches may be important for ranking.…”

Section: Related Workmentioning

confidence: 99%

Building an Argument Search Engine for the Web

Wachsmuth¹,

Potthast²,

Khatib³

et al. 2017

Proceedings of the 4th Workshop on Argument Mining

119

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Computational argumentation is expected to play a critical role in the future of web search. To make this happen, many searchrelated questions must be revisited, such as how people query for arguments, how to mine arguments from the web, or how to rank them. In this paper, we develop an argument search framework for studying these and further questions. The framework allows for the composition of approaches to acquiring, mining, assessing, indexing, querying, retrieving, ranking, and presenting arguments while relying on standard infrastructure and interfaces. Based on the framework, we build a prototype search engine, called args, that relies on an initial, freely accessible index of nearly 300k arguments crawled from reliable web resources. The framework and the argument search engine are intended as an environment for collaborative research on computational argumentation and its practical evaluation.

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Section: Related Workmentioning

confidence: 99%

Building an Argument Search Engine for the Web

Wachsmuth¹,

Potthast²,

Khatib³

et al. 2017

Proceedings of the 4th Workshop on Argument Mining

119

View full text Add to dashboard Cite

show abstract

“…Although the verifiability of propositions enables to determine appropriate types of support, it does not answer if an argument is sufficiently supported or not. Persing and Ng (2015) introduced an approach for recognizing the argumentation strength of an essay. They found that pos n-grams, prompt adherence features, and predicted argument components perform best.…”

Section: Related Workmentioning

confidence: 99%

“…These existing approaches either identify undisputed arguments in online communities (Cabrio and Villata, 2012), assess the persuasiveness of arguments (Wei et al, 2016), compare and rank arguments regarding their convincingness (Habernal and Gurevych, 2016b), or summarize the argumentation strength of an entire essay in a single holistic score (Persing and Ng, 2015). Our approach is based on the theoretical framework proposed by Johnson and Blair (2006).…”

Section: Introductionmentioning

confidence: 99%

Recognizing Insufficiently Supported Arguments in Argumentative Essays

Stab¹,

Gurevych²

2017

Proceedings of the 15th Conference of the European Chapter of The Association for Computational Linguistics: Volume 1

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In this paper, we propose a new task for assessing the quality of natural language arguments. The premises of a well-reasoned argument should provide enough evidence for accepting or rejecting its claim. Although this criterion, known as sufficiency, is widely adopted in argumentation theory, there are no empirical studies on its applicability to real arguments. In this work, we show that human annotators substantially agree on the sufficiency criterion and introduce a novel annotated corpus. Furthermore, we experiment with feature-rich SVMs and convolutional neural networks and achieve 84% accuracy for automatically identifying insufficiently supported arguments. The final corpus as well as the annotation guideline are freely available for encouraging future research on argument quality. 1

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“…Larkey (Larkey, 1998) (Persing and Ng, 2015), discourse structure of essays (Song et al, 2015) (Stab and Gurevych, 2014) , and grammar correction in general (Rozovskaya and Roth, 2014) (Lee et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

A Multi-aspect Analysis of Automatic Essay Scoring for Brazilian Portuguese

Amorim

Veloso

2017

Proceedings of the Student Research Workshop at the 15th Conference Of the European Chapter of the Association for Co

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While several methods for automatic essay scoring (AES) for the English language have been proposed, systems for other languages are unusual. To this end, we propose in this paper a multi-aspect AES system for Brazilian Portuguese which we apply to a collection of essays, which human experts evaluated according to the five aspects defined by the Brazilian Government for the National High School Exam (ENEM). These aspects are skills that student must master and every skill is assessed separately from one another.In addition to prediction, we also performed feature analysis for each aspect. The proposed AES system employs several features already used by AES systems for the English language. Our results show that predictions for some aspects performed well with the employed features, while predictions for other aspects performed poorly.Furthermore, the detailed feature analysis we performed made it possible to note their independent impacts on each of the five aspects. Finally, aside from these contributions, our work reveals some challenges and directions for future research, related, for instance, to the fact that the ENEM has over eight million yearly enrollments.

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Modeling Argument Strength in Student Essays

Cited by 120 publications

References 16 publications

Building an Argument Search Engine for the Web

Building an Argument Search Engine for the Web

Recognizing Insufficiently Supported Arguments in Argumentative Essays

A Multi-aspect Analysis of Automatic Essay Scoring for Brazilian Portuguese

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