Approaching Language Transfer through Text Classification

Scott Jarvis

ISBN 10: 1847696988 / ISBN 13: 9781847696984

Published by Channel View Publications Ltd, GB, 2012

About this Item

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.

Seller Inventory # LU-9781847696984

Bibliographic Details

• Title: Approaching Language Transfer through Text Classification
• Publisher: Channel View Publications Ltd, GB
• Publication Date: 2012
• Language: English
• ISBN 10: 1847696988
• ISBN 13: 9781847696984
• Binding: Hardback
• Condition: New
• Weight: 460 grams

About this title

Synopsis

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.

About the Authors

Scott Jarvis is Professor of Linguistics at the University of Utah, USA. His areas of research include crosslinguistic influence and lexical diversity. He is the co-editor (with Scott Crossley) of Approaching Language Transfer through Text Classification (2012).

Scott A. Crossley is an Assistant Professor at Georgia State University. His work involves the application of natural language processing theories and approaches for investigating second language acquisition, text readability, and writing proficiency. His current research interests include lexical proficiency, writing quality, and text coherence and processing.