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A Study On The Distribution Of Dependency Distances In Different Domains Of Written English In The BNC

Posted on:2016-03-04Degree:MasterType:Thesis
Country:ChinaCandidate:Y Q WangFull Text:PDF
GTID:2285330470978598Subject:Foreign Linguistics and Applied Linguistics
Abstract/Summary:PDF Full Text Request
Modern Dependency Grammar, primarily attributed to the seminal work of Lucien Tesniere, connects individual words which have grammatical functions with respect to each other in a sentence. Features of dependency relations are as follows. Firstly, it is a binary relation between two linguistic units. Secondly, it is usually asymmetrical, with one of the two units acting as the governor and the other as dependent. Thirdly, the relation is labeled and the type of a dependency relation is usually indicated using a label on top of the arc linking the two units. This thesis is corpus-based and employs both quantitative and qualitative methods, aiming to study varieties of English, namely, different registers and genres of English based on dependency grammar. It computes and analyzes the distribution of dependency distances in nine domains of written English, namely, applied science, arts, belief, commerce, imaginative, leisure, natural science, social science and world affairs, in the British National Corpus.The result of the study shows that the mean dependency distance (MDD) of the applied science domain is the greatest, while that of the imaginative domain is the smallest. Imaginative texts are less difficult than texts in applied science. Difference between absolute dependency distances (ADDs) of the imaginative domain and those of the other eight domains is highly significant. With regard to dependency directions, English is a language where the dependent tend to occur on either side of the head. The applied science domain, arts domain, commerce domain and imaginative domain have a tendency to be positive (governor-final), while the belief domain, leisure domain, social science domain, natural science and world affairs domain are more likely to be negative (governor-initial). When it comes to dependency types, ten dominant domain dependency types in all the domains are advmod (adverbial modifier), amod (adjectival modifier), aux (auxiliary), conj (conjunct), dobj (direct object), det (determiner), nn (noun compound modifier), nsubj (nominal subject), pobj (object of a preposition), prep (prepositional modifier). Of these ten types, the most frequent dependency type is nsubj in the imaginative domain while prep is the most frequent in the other eight domains. Regarding dependency directions, four grammatical relations are governor-initial, namely, prep, pobj, dobj, conj. Generally, dependency types in the applied science domain, the arts domain, the commerce domain, and the natural science domain have longer MDDs, while those of the imaginative domain have shorter MDDs.
Keywords/Search Tags:Dependency Distance, Quantitative Linguistics, Corpus, Domain, Written English
PDF Full Text Request
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