03823nam 2200685 a 450 991081816440332120240516204847.0978184769699197866137704481-84769-699-610.21832/9781847696991(CKB)2550000000108262(EBL)977734(OCoLC)806204967(MiAaPQ)EBC977734(DE-B1597)491364(OCoLC)1043622844(DE-B1597)9781847696991(Au-PeEL)EBL977734(CaPaEBR)ebr10582794(CaONFJC)MIL377044(EXLCZ)99255000000010826220111130d2012 uy 0engur|n|---|||||txtrdacontentcrdamediacrrdacarrierApproaching language transfer through text classification explorations in the detection-based approach /edited by Scott Jarvis and Scott A. Crossley1st ed.Bristol ;Buffalo Multilingual Mattersc20121 online resource (196 p.)Second language acquisition ;64Description based upon print version of record.Includes bibliographical references.Frontmatter --Contents --Contributors --1. The Detection-Based Approach: An Overview --2. Detecting L2 Writers’ L1s on the Basis of Their Lexical Styles --3. Exploring the Role of n-Grams in L1 Identification --4. Detecting the First Language of Second Language Writers Using Automated Indices of Cohesion, Lexical Sophistication, Syntactic Complexity and Conceptual Knowledge --5. Error Patterns and Automatic L1 Identification --6. The Comparative and Combined Contributions of n-Grams, Coh-Metrix Indices and Error Types in the L1 Classification of Learner Texts --7. Detection-Based Approaches: Methods, Theories and ApplicationsRecent work has pointed to the need for a detection-based approach to transfer capable of discovering elusive crosslinguistic effects through the use of human judges and computer classifiers that can learn to predict learners’ language backgrounds based on their patterns of language use. This book addresses that need. It details the nature of the detection-based approach, discusses how this approach fits into the overall scope of transfer research, and discusses the few previous studies that have laid the groundwork for this approach. The core of the book consists of five empirical studies that use computer classifiers to detect the native-language affiliations of texts written by foreign language learners of English. The results highlight combinations of language features that are the most reliable predictors of learners’ language backgrounds.Second language acquisition (Clevedon, England) ;64.Language transfer (Language learning)English languageRhetoricStudy and teachingcomputer classifiers to detect language background.crosslinguistic influence in SLA.crosslinguistic influence.detection-based approach.learners’ native-language backgrounds.transfer in SLA.transfer in language learning.Language transfer (Language learning)English languageRhetoricStudy and teaching.401/.93ES 760rvkJarvis Scott1966-1622357Crossley Scott A1622358MiAaPQMiAaPQMiAaPQBOOK9910818164403321Approaching language transfer through text classification3956180UNINA