TY  - BOOK
AU  - Bestgen,Yves
AU  - Castañeda-Jiménez,Gabriela
AU  - Crossley,Scott A.
AU  - Granger,Sylviane
AU  - Jarvis,Scott
AU  - McNamara,Danielle
AU  - McNamara,Danielle S.
AU  - Nielsen,Rasmus
AU  - Paquot,Magali
AU  - Thewissen,Jennifer
TI  - Approaching Language Transfer through Text Classification: Explorations in the Detection-based Approach 
T2  - Second Language Acquisition
SN  - 9781847696984
AV  - P130.5 .A66 2012
U1  - 401/.93 
PY  - 2012///]
CY  - Bristol, Blue Ridge Summit : 
PB  - Multilingual Matters, 
KW  - English language
KW  - Rhetoric
KW  - Study and teaching
KW  - Language transfer (Language learning)
KW  - LANGUAGE ARTS & DISCIPLINES / Linguistics / Psycholinguistics
KW  - bisacsh
KW  - computer classifiers to detect language background
KW  - crosslinguistic influence in SLA
KW  - crosslinguistic influence
KW  - detection-based approach
KW  - learners’ native-language backgrounds
KW  - transfer in SLA
KW  - transfer in language learning
N1  - 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 Applications; restricted access
N2  - Recent 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
UR  - https://doi.org/10.21832/9781847696991
UR  - https://www.degruyter.com/isbn/9781847696991
UR  - https://www.degruyter.com/document/cover/isbn/9781847696991/original
ER  -