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ERIC Number: ED525272
Record Type: Non-Journal
Publication Date: 2011
Pages: 275
Abstractor: As Provided
Reference Count: 0
ISBN: ISBN-978-1-1244-9219-3
Factors Predicting the Use of Passive Voice in Newspaper Headlines
Micciulla, Linnea Margaret
ProQuest LLC, Ph.D. Dissertation, Boston University
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. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page:]
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Publication Type: Dissertations/Theses - Doctoral Dissertations
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A