Cluster Analysis Based on Contextual Features Extraction for Conversational Corpus
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Cluster analysis related to computational linguistics seldom concerned with Pragmatics level. Features of corpus on Pragmatics level related to specific situations, including backgrounds, titles and habits. To improve the accuracy of clustering for conversations collected from international students in Tsinghua University, it required contextual features. Here, we collected four-hundred conversations as a corpus and built it to Vector Space Model. With the Oxford-Duden Dictionary and other methods we modified the model and concluded into three groups. We testified our hypothesis through self-organizing map neural network. The result suggested that the modified model had a better outcome.Keywords:
Corpus Linguistics
Computational linguistics
Pragmatics is a new-developing science in the field of linquistics.Pragmatics is a science different from semantics .Pragmatics relys on the capability of the practical use of the language communication,while the language expression depends on its context which is the key factor in the speech situation.The usual practice of a speech has a particular significance in pragmatics.
Expression (computer science)
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Pragmatics in the field of English language teaching has recently received increasing research interests, but studies on teachers learning to teach pragmatics are limited. The present study extends this research agenda by investigating how well second/foreign language preservice teacher education (SLPTE) prepares teachers to teach pragmatics. Adopting a multi-site case study approach, this study examines (1) the representation of pragmatics and instructional pragmatics in SLPTE programmes at Australian and Vietnamese universities, and (2) programme leaders’ beliefs about pragmatics instructor preparation. Data were collected from curriculum document analysis, a questionnaire, and four individual semi-structured interviews. The findings show that pragmatics was represented to different extents across the programmes but instructional pragmatics was entirely absent. The findings further show three sets of the programme leaders’ beliefs: (1) preservice teachers were not well-prepared to teach pragmatics; (2) teaching pragmatics and instructional pragmatics to preservice teachers is important; and (3) pragmatics and instructional pragmatics need to be sufficiently addressed in SLPTE. The study has important implications for teacher educators, curriculum designers, and relevant stakeholders regarding L2 pragmatics teacher preparation.
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The Handbook of Pragmatics(2004)by Horn and Ward consists of four parts.The second part Pragmatics and Discourse Structure is about a relatively unfamiliar topic.An analysis of the papers in the second part suggests that there is a discursive turn in pragmatics.This characterization can be verified by the editors' area and the related papers in the other parts.However,considering the relation between pragmatics and discourse analysis,it is perhaps more accurate to say that the recent trend in pragmatics is a return,rather than turn,to discourse.
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Pragmatics is one of the most vibrant and rapidly growing fields in linguistics and the philosophy of language. It is a particularly complex subject with all kinds of disciplinary influences and few, if any, clear boundaries. This chapter provides an authoritative, comprehensive, and up-to-date overview of the contemporary landscape of pragmatics. It starts with the question of what is pragmatics. It then surveys the two main schools of thought in pragmatics: the Anglo-American and European Continental traditions. This is followed by a review of macro-pragmatics, which covers cognitively oriented macro-pragmatics, such as experimental, computational, and clinical pragmatics; socially and/or culturally oriented macro-pragmatics, such as politeness and impoliteness studies, cultural, cross- and intercultural, and interpersonal pragmatics; and those branches of macro-pragmatics that are not easily and/or neatly placed in the first two categories, such as historical, corpus, and literary pragmatics. The final section addresses the organization and content of this handbook.
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Corpus analysis can be expanded and scaled up by incorporating computational methods from natural language processing. This Element shows how text classification and text similarity models can extend our ability to undertake corpus linguistics across very large corpora. These computational methods are becoming increasingly important as corpora grow too large for more traditional types of linguistic analysis. We draw on five case studies to show how and why to use computational methods, ranging from usage-based grammar to authorship analysis to using social media for corpus-based sociolinguistics. Each section is accompanied by an interactive code notebook that shows how to implement the analysis in Python. A stand-alone Python package is also available to help readers use these methods with their own data. Because large-scale analysis introduces new ethical problems, this Element pairs each new methodology with a discussion of potential ethical implications.
Python
Corpus Linguistics
Computational linguistics
Text corpus
Sociolinguistics
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Corpus linguistics has been closely intertwined with digital technology since the introduction of university computer mainframes in the 1960s. Making use of both digitized data in the form of the language corpus and computational methods of analysis involving concordancers and statistics software, corpus linguistics arguably has a place in the digital humanities. Still, it remains obscure and fi gures only sporadically in the literature on the digital humanities. Th is article provides an overview of the main principles of corpus linguistics and the role of computer technology in relation to data and method and also off ers a bird's-eye view of the history of corpus linguistics with a focus on its intimate relationship with digital technology and how digital technology has impacted the very core of corpus linguistics and shaped the identity of the corpus linguist. Ultimately, the article is oriented towards an acknowledgment of corpus linguistics' alignment with the digital humanities.
Corpus Linguistics
Digital Humanities
Computational linguistics
Text corpus
Media linguistics
Text Linguistics
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This article introduces the linguistic subdiscipline of pragmatics and shows how this is being applied to the development of spoken dialogue systems — currently perhaps the most important applications area for computational pragmatics. It traces the history of pragmatics from its philosophical roots, and outlines some key notions of theoretical pragmatics — speech acts, illocutionary force, the cooperative principle and relevance. It then discusses the application of pragmatics to dialogue modelling, especially the development of spoken dialogue systems intended to interact with human beings in task-oriented scenarios such as providing travel information and shows how and why computational pragmatics differs from ‘linguistic’ pragmatics, and how pragmatics contributes to the computational analysis of dialogues. One major illustration of this is the application of speech act theory in the analysis and synthesis of service interactions in terms of dialogue acts.
Relevance theory
Relevance
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Computational linguistics
Corpus Linguistics
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Abstract This paper highlights areas of concern in the assessment of pragmatics, with the intent of stimulating fresh thinking about the assessment of pragmatics both for research purposes and as a part of classroom instruction. It starts by considering what aspects of ability in pragmatics to assess, and then contrasts the trade-off between the feasibility of obtaining data and the ultimate importance of the data. Next, the conspicuous lack of assessment of ability in L2 pragmatics in language classes is noted. Then follow sections on topics all relating primarily to the assessment of pragmatics for research purposes – the use of mixed methods, data elicitation procedures, and norms used in determining the appropriateness of any given performance in pragmatics. The last two topics deal, respectively, with the perceived relevance of the given assessment by the learners and with the value of collecting verbal report data from the respondents as a means for validating the assessment measures. Finally, considerations regarding the most prominent of these issues are provided.
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Value (mathematics)
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A growing number of studies report interesting insights gained from existing data resources. Among those, there are analyses on textual data, giving reason to consider such methods for linguistics as well. However, the field of corpus linguistics usually works with purposefully collected, representative language samples that aim to answer only a limited set of research questions.
This thesis aims to shed some light on the potentials of data-driven analysis based on machine learning and predictive modelling for corpus linguistic studies, investigating the possibility to repurpose existing German language corpora for linguistic inquiry by using methodologies developed for data science and computational linguistics. The study focuses on predictive modelling and machine-learning-based data mining and gives a detailed overview and evaluation of currently popular strategies and methods for analysing corpora with computational methods.
After the thesis introduces strategies and methods that have already been used on language data, discusses how they can assist corpus linguistic analysis and refers to available toolkits and software as well as to state-of-the-art research and further references, the introduced methodological toolset is applied in two differently shaped corpus studies that utilize readily available corpora for German. The first study explores linguistic correlates of holistic text quality ratings on student essays, while the second deals with age-related language features in computer-mediated communication and interprets age prediction models to answer a set of research questions that are based on previous research in the field. While both studies give linguistic insights that integrate into the current understanding of the investigated phenomena in German language, they systematically test the methodological toolset introduced beforehand, allowing a detailed discussion of added values and remaining challenges of machine-learning-based data mining methods in corpus at the end of the thesis.
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Text corpus
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