Using Grammatical Features for Automatic Register Identification in an Unrestricted Corpus of Documents from the Open Web. (9th January 2016)

• Record Type: Journal Article
• Authors: Biber, Douglas; Egbert, Jesse
• Is Part Of: Journal of research design and statistics in linguistics and communication science. Volume 2:Number 1(2015)
• Page Start: 3
• Page End: 36
• Publication Date: 2016-01-09
• Subjects: automatic genre identification (agi) -- discriminant analysis -- web registers -- text classification; Linguistics -- Research -- Periodicals; Linguistics -- Statistical methods -- Periodicals; Mathematical linguistics -- Periodicals; 410.72
• DOI: 10.1558/jrds.v2i1.27637
• Languages: English
• ISSNs: 2052-417X

Abstract

Abstract : Most previous attempts at automatic genre identification have been based on corpus samples that are relatively small and artificially restricted. In this study we set out to automatically predict register/genre categories in a large, representative sample of documents from the open web using a linguistic approach focused on lexico-grammatical characteristics that have functional associations. Our findings demonstrate the possibility of automatically predicting register/genre on the unrestricted open web, and we anticipate that future extensions will allow this task to be accomplished with considerably higher degrees of accuracy.