881 resultados para Text linguistics


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Communication in Forensic Contexts provides in-depth coverage of the complex area of communication in forensic situations. Drawing on expertise from forensic psychology, linguistics and law enforcement worldwide, the text bridges the gap between these fields in a definitive guide to best practice. •Offers best practice for understanding and improving communication in forensic contexts, including interviewing of victims, witnesses and suspects, discourse in courtrooms, and discourse via interpreters •Bridges the knowledge gaps between forensic psychology, forensic linguistics and law enforcement, with chapters written by teams bringing together expertise from each field •Published in collaboration with the International Investigative Interviewing Research Group, dedicated to furthering evidence-based practice and practice-based research amongst researchers and practitioners •International, cross-disciplinary team includes contributors from North America, Europe and Asia Pacific, and from psychology, linguistics and forensic practice

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Starting with a description of the software and hardware used for corpus linguistics in the late 1980s to early 1990s, this contribution discusses difficulties faced by the software designer when attempting to allow users to study text. Future human-machine interfaces may develop to be much more sophisticated, and certainly the aspects of text which can be studied will progress beyond plain text without images. Another area which will develop further is the study of patternings involving not just single words but word-relations across large stretches of text.

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Much has been written on the organizational power of metaphor in discourse, eg on metaphor ‘chains’ and ‘clusters’ of linguistic metaphor in discourse (Koller 2003, Cameron & Stelma 2004, Semino 2008) and the role of extended and systematic metaphor in organizing long stretches of language, even whole texts (Cameron et al 2009, Cameron & Maslen 2010, Deignan et al 2013, Semino et al 2013). However, at times, this work belies the intricacies of how a single metaphoric idea can impact on a text. The focus of this paper is a UK media article derived from a HM Treasury press release on alleviating poverty. The language of the article draws heavily on orientational (spatial) metaphors, particularly metaphors of movement around GOOD IS UP. Although GOOD IS UP can be considered a single metaphoric idea, the picture the reader builds up as they move line by line through this text is complex and multifaceted. I take the idea of “building up a picture” literally in order to investigate the schema of motion relating to GOOD IS UP. To do this, fifteen informants (Masters students at a London university), tutored in Cognitive Metaphor Theory, were asked to read the article and underline words and expressions they felt related to GOOD IS UP. The text was then read back to the informant with emphasis given to the words they had underlined, while they drew a pictorial representation of the article based on the meanings of these words, integrating their drawings into a single picture as they went along. I present examples of the drawings the informants produced. I propose that using Metaphor-led Discourse Analysis to produce visual material in this way offers useful insights into how metaphor contributes to meaning making at text level. It shows how a metaphoric idea, such as GOOD IS UP, provides the text producer with a rich and versatile meaning-making resource for constructing text; and gives a ‘mind-map’ of how certain aspects of a media text are decoded by the text receiver. It also offers a partial representation of the elusive, intermediate ‘deverbalized’ stage of translation (Lederer 1987), where the sense of the source text is held in the mind before it is transferred to the target language. References Cameron, L., R. Maslen, Z. Todd, J. Maule, P. Stratton & N. Stanley. 2009. ‘The discourse dynamic approach to metaphor and metaphor-led analysis’. Metaphor and Symbol, 24(2), 63-89. Cameron, L. & R. Maslen (eds). 2010. Metaphor Analysis: Research Practice in Applied Linguistics, Social Sciences and Humanities. London: Equinox. Cameron, L. & J. Stelma. 2004. ‘Metaphor Clusters in Discourse’. Journal of Applied Linguistics, 1(2), 107-136. Deignan, A., J. Littlemore & E. Semino. 2013. Figurative Language, Genre and Register. Cambridge: Cambridge University Press. Koller, V. 2003. ‘Metaphor Clusters, Metaphor Chains: Analyzing the Multifunctionality of Metaphor in Text’. metaphorik.de, 5, 115-134. Lederer, M. 1987. ‘La théorie interprétative de la traduction’ in Retour à La Traduction. Le Francais dans Le Monde. Semino, E. 2008. Metaphor in Discourse. Cambridge: Cambridge University Press. Semino, E., A. Deignan & J. Littlemore. 2013. ‘Metaphor, Genre, and Recontextualization’. Metaphor and Symbol. 28(1), 41-59.

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Thesis (Ph.D.)--University of Washington, 2016-08

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Human relationships have long been studied by scientists from domains like sociology, psychology, literature, etc. for understanding people's desires, goals, actions and expected behaviors. In this dissertation we study inter-personal relationships as expressed in natural language text. Modeling inter-personal relationships from text finds application in general natural language understanding, as well as real-world domains such as social networks, discussion forums, intelligent virtual agents, etc. We propose that the study of relationships should incorporate not only linguistic cues in text, but also the contexts in which these cues appear. Our investigations, backed by empirical evaluation, support this thesis, and demonstrate that the task benefits from using structured models that incorporate both types of information. We present such structured models to address the task of modeling the nature of relationships between any two given characters from a narrative. To begin with, we assume that relationships are of two types: cooperative and non-cooperative. We first describe an approach to jointly infer relationships between all characters in the narrative, and demonstrate how the task of characterizing the relationship between two characters can benefit from including information about their relationships with other characters in the narrative. We next formulate the relationship-modeling problem as a sequence prediction task to acknowledge the evolving nature of human relationships, and demonstrate the need to model the history of a relationship in predicting its evolution. Thereafter, we present a data-driven method to automatically discover various types of relationships such as familial, romantic, hostile, etc. Like before, we address the task of modeling evolving relationships but don't restrict ourselves to two types of relationships. We also demonstrate the need to incorporate not only local historical but also global context while solving this problem. Lastly, we demonstrate a practical application of modeling inter-personal relationships in the domain of online educational discussion forums. Such forums offer opportunities for its users to interact and form deeper relationships. With this view, we address the task of identifying initiation of such deeper relationships between a student and the instructor. Specifically, we analyze contents of the forums to automatically suggest threads to the instructors that require their intervention. By highlighting scenarios that need direct instructor-student interactions, we alleviate the need for the instructor to manually peruse all threads of the forum and also assist students who have limited avenues for communicating with instructors. We do this by incorporating the discourse structure of the thread through latent variables that abstractly represent contents of individual posts and model the flow of information in the thread. Such latent structured models that incorporate the linguistic cues without losing their context can be helpful in other related natural language understanding tasks as well. We demonstrate this by using the model for a very different task: identifying if a stated desire has been fulfilled by the end of a story.

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This dissertation applies statistical methods to the evaluation of automatic summarization using data from the Text Analysis Conferences in 2008-2011. Several aspects of the evaluation framework itself are studied, including the statistical testing used to determine significant differences, the assessors, and the design of the experiment. In addition, a family of evaluation metrics is developed to predict the score an automatically generated summary would receive from a human judge and its results are demonstrated at the Text Analysis Conference. Finally, variations on the evaluation framework are studied and their relative merits considered. An over-arching theme of this dissertation is the application of standard statistical methods to data that does not conform to the usual testing assumptions.

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In this article, we take a close look at the literacy demands of one task from the ‘Marvellous Micro-organisms Stage 3 Life and Living’ Primary Connections unit (Australian Academy of Science, 2005). One lesson from the unit, ‘Exploring Bread’, (pp 4-8) asks students to ‘use bread labels to locate ingredient information and synthesise understanding of bread ingredients’. We draw upon a framework offered by the New London Group (2000), that of linguistic, visual and spatial design, to consider in more detail three bread wrappers and from there the complex literacies that students need to interrelate to undertake the required task. Our findings are that although bread wrappers are an example of an everyday science text, their linguistic, visual and spatial designs and their interrelationship are not trivial. We conclude by reinforcing the need for teachers of science to also consider how the complex design elements of everyday science texts and their interrelated literacies are made visible through instructional practice.