22,158 research outputs found

    Predicting the Law Area and Decisions of French Supreme Court Cases

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    In this paper, we investigate the application of text classification methods to predict the law area and the decision of cases judged by the French Supreme Court. We also investigate the influence of the time period in which a ruling was made over the textual form of the case description and the extent to which it is necessary to mask the judge's motivation for a ruling to emulate a real-world test scenario. We report results of 96% f1 score in predicting a case ruling, 90% f1 score in predicting the law area of a case, and 75.9% f1 score in estimating the time span when a ruling has been issued using a linear Support Vector Machine (SVM) classifier trained on lexical features.Comment: RANLP 201

    Persuasive argumentation as a cultural practice

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    In this article author traces relation between argumentation and cultural practice. The first part focuses on definition of argumentation in informal logic tradition. In particular, it discusses argument in terms of verbal and social activity involving the use of everyday language. Author claims that there is no argumentation beyond language. The second part explains persuasive argumentation as a form of cultural practice. The persuasive arguments found in “social practice” can be understood as a social activity, analysable within the context of a given cultural system. Author refers to an approach taking the argumentative expression as a certain type of communicative practice, directed towards respecting, recognising or accepting specific actions. The inclusion of persuasive argumentation in the “circuit of cultural activities” to be studied makes it possible to compare this type of argumentation with other social practices, and to posit a clear historical dimension in the study of argumentation. It also makes it possible to view persuasive argumentation as one of many cultural activities aimed at changing or perpetuating behaviours, attitudes, thinking, etc. The third part of the paper concerns the problem of humanistic interpretation of persuasive argumentation. Author attempts to develop this intuition, at the same time demonstrating the problems that arise from this approach. In conclusion, author tries to analyze argumentation in terms of culture theory and humanistic interpretation

    How did the discussion go: Discourse act classification in social media conversations

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    We propose a novel attention based hierarchical LSTM model to classify discourse act sequences in social media conversations, aimed at mining data from online discussion using textual meanings beyond sentence level. The very uniqueness of the task is the complete categorization of possible pragmatic roles in informal textual discussions, contrary to extraction of question-answers, stance detection or sarcasm identification which are very much role specific tasks. Early attempt was made on a Reddit discussion dataset. We train our model on the same data, and present test results on two different datasets, one from Reddit and one from Facebook. Our proposed model outperformed the previous one in terms of domain independence; without using platform-dependent structural features, our hierarchical LSTM with word relevance attention mechanism achieved F1-scores of 71\% and 66\% respectively to predict discourse roles of comments in Reddit and Facebook discussions. Efficiency of recurrent and convolutional architectures in order to learn discursive representation on the same task has been presented and analyzed, with different word and comment embedding schemes. Our attention mechanism enables us to inquire into relevance ordering of text segments according to their roles in discourse. We present a human annotator experiment to unveil important observations about modeling and data annotation. Equipped with our text-based discourse identification model, we inquire into how heterogeneous non-textual features like location, time, leaning of information etc. play their roles in charaterizing online discussions on Facebook

    A Framework for Combining Defeasible Argumentation with Labeled Deduction

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    In the last years, there has been an increasing demand of a variety of logical systems, prompted mostly by applications of logic in AI and other related areas. Labeled Deductive Systems (LDS) were developed as a flexible methodology to formalize such a kind of complex logical systems. Defeasible argumentation has proven to be a successful approach to formalizing commonsense reasoning, encompassing many other alternative formalisms for defeasible reasoning. Argument-based frameworks share some common notions (such as the concept of argument, defeater, etc.) along with a number of particular features which make it difficult to compare them with each other from a logical viewpoint. This paper introduces LDSar, a LDS for defeasible argumentation in which many important issues concerning defeasible argumentation are captured within a unified logical framework. We also discuss some logical properties and extensions that emerge from the proposed framework.Comment: 15 pages, presented at CMSRA Workshop 2003. Buenos Aires, Argentin

    THE USE OF COHESIVE DEVICES IN RELATION TO THE QUALITY OF THE STUDENTS’ ARGUMENTATIVE WRITING

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    The ability to compose an argumentative text is important for ESL and EFL learners. In terms of the communicative nature of writing, cohesion is regarded as an essential textual component, not only to create organized text but also to the comprehensiveness of the text. Therefore, the use of cohesive devices is really important. Based on Halliday and Hasan Cohesion theory (1976)this study is intended to investigate the use of cohesive devices and also the relationship between the frequency of cohesive devices using and the quality of argumentative writing. An analysis of 30 students’ argumentative writing showed that the students were familiar with various cohesive devices and used them in their writing. Among the cohesive devices, reference had the largest percentage of the total number cohesive devices, followed by lexical devices and conjunction devices. Furthermore, it was found that there was no significant relationship between the number of cohesive devi ces used and the quality of writing. The findings of the study have some important implications for EFL writing teachers and learners

    Exploring the interplay of mode of discourse and proficiency level in ESL writing performance

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    Recent theory in discourse and practice in rhetoric has suggested that writers require different skills and strategies when writing for different purposes, and in using different genres and modes (Kinneavy, 1972; Carrell and Connor, 1991) in writing. The importance of taking into account these various aspectual skills and forms of writing is recognised in teaching (e.g. Scarcella and Oxford, 1992), and in the assessment of writing (e.g. Odell and Cooper, 1980). For instance, Odell and Cooper argued that any claims about writing ability cannot be made until students’ performance on a variety of writing tasks has been examined. Thus, the issue of what writing task(s) are to be included in a test is crucial, since a task will be regarded as useless if it does not provide the basis for making generalisations regarding an individual’s writing ability. This paper presents the findings of a study on the effects of mode of discourse on L2 writing performance as well as the interplay between learner variable, namely, proficiency level and task variable, mode of discourse amongst Malaysian upper secondary ESL learners. The findings provide some evidence for the need to re-examine issues of reliability and validity in test practice of manipulating variables in the design of assessment tasks to evaluate ESL writing performance. Given the status and complexity of the writing skill, it stands to reason that studies into this area will continue to shed light onto how best the construct can be understood, taught and tested to give a fair chance for language learners to exhibit their true ability and be reliably reported on
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