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Factors predicting the use of passive voice in newspaper headlines.

机译:预测报纸头条使用被动语态的因素。

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摘要

Information packaging researchers have found that certain factors influence active/passive voice alternations: Animacy, Definiteness and Weight influence argument order and thus choice of voice. Researchers in Critical Discourse Analysis (CDA) and psycholinguistics claim that voice is influenced by social factors, e.g. gender, social standing, or political bias. This dissertation draws from these distinct perspectives to perform probabilistic analysis of factors predicting voice in newspaper headlines, a novel research area for information packaging, and a rich source of data relevant to CDA.;In the first study to examine the relative contributions of these two types of constraints, this dissertation explores the predictive values of Animacy, Definiteness and Weight, as well as four social constraints: Gender, Nationality, Age and "Badness." It also investigates using combined human and automated methods for quick and accurate data annotation. The corpus consists of US newspaper headlines published between 2002 and 2007 containing one of twelve selected verbs: accuse, aid, anger, create, encourage, frustrate, hit, hurt, injure, inspire, kill and shoot.;The Animacy, Definiteness and Weight hierarchies predict that animate arguments tend to precede inanimate arguments, definite arguments tend to precede less definite arguments, and shorter arguments tend to precede longer arguments, respectively (Quirk et al. 1972, Ransom 1979, inter alia). The present findings support these hierarchies. Of the linguistic factors, Animacy has the strongest effect. Of the social factors, Nationality and Age are not significant predictors of voice, while Badness is a significant predictor. A "Bad" argument has an increased likelihood of occurring post-verbally relative to other arguments, so that a "Bad" Actor predicts passive, while a "Bad" Undergoer predicts active voice. Gender has a marginally significant effect which differs by verb; overall, arguments with a Female Actor are likely to occur with active voice relative to Male Actors; when the verb is kill, Female Undergoers are relatively more likely to occur with active voice.;The findings indicate that both social factors and traditional linguistic constraints predict voice. The results show that including social factors improves probabilistic models of grammar, and that analyses which include both linguistic and social factors provide better support for empirical claims.
机译:信息包装研究人员发现,某些因素会影响主动/被动语音的交替:动画性,确定性和权重会影响论证顺序,从而影响语音的选择。批评性话语分析(CDA)和心理语言学的研究人员声称,声音受社交因素(例如,性别,社会地位或政治偏见。本文从这些不同的角度出发,对报纸头条中预测语音的因素进行概率分析,一个新颖的信息包装研究领域以及与CDA相关的丰富数据来源。在第一个研究中,研究了这两个方面的相对贡献约束类型,本文探讨了动画性,确定性和权重的预测值,以及四个社会约束:性别,国籍,年龄和“不良”。它还调查使用人工和自动化的组合方法进行快速准确的数据注释。语料库由2002年至2007年间发布的美国报纸头条组成,包含十二种选定的动词之一:控告,帮助,愤怒,创造,鼓励,挫败,打击,伤害,伤害,启发,杀死和射击。层次结构预测,有生命的论点倾向于先于无生命的论点,确定的论点倾向于在较少的确定的论点之前,而较短的论点往往在较长的论点之前(Quirk等,1972; Ransom,1979)。本调查结果支持这些层次结构。在语言因素中,“ Animacy”效果最强。在社会因素中,国籍和年龄不是语音的重要预测因素,而不良则是语音的重要预测因素。相对于其他参数,“不良”自变量在口后发生的可能性增加,因此“不良”演员会预测为被动,而“不良”演员会预测为主动语态。性别具有轻微的重要影响,因动词而异;总体而言,与男演员相比,与男演员的争吵很有可能会发声。当动词被杀死时,女性下属相对更有可能以主动语态出现。研究结果表明,社会因素和传统语言限制都可以预测语态。结果表明,包括社会因素可以改善语法的概率模型,同时包括语言和社会因素在内的分析为经验主张提供更好的支持。

著录项

  • 作者

    Micciulla, Linnea Margaret.;

  • 作者单位

    Boston University.;

  • 授予单位 Boston University.;
  • 学科 Language Linguistics.;Journalism.;Language General.
  • 学位 Ph.D.
  • 年度 2011
  • 页码 250 p.
  • 总页数 250
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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