New version page

review3

Upgrade to remove ads

This preview shows page 1-2-3 out of 8 pages.

Save
View Full Document
Premium Document
Do you want full access? Go Premium and unlock all 8 pages.
Access to all documents
Download any document
Ad free experience
Premium Document
Do you want full access? Go Premium and unlock all 8 pages.
Access to all documents
Download any document
Ad free experience
Premium Document
Do you want full access? Go Premium and unlock all 8 pages.
Access to all documents
Download any document
Ad free experience

Upgrade to remove ads
Unformatted text preview:

Language Learning & Technology http://llt.msu.edu/vol10num1/review3/ January, 2006, Volume 10, Number 1 pp. 30-37 Copyright © 2006, ISSN 1094-3501 30 REVIEW OF THREE SOFTWARE PROGRAMS DESIGNED TO IDENTIFY LEXICAL BUNDLES Title KfNgram 1.2.03 N-Gram Phrase Extractor (Compleat Lexical Tutor 4.0) Wordsmith Tools 3 Platform PC (download) PC (use on Web site) PC (download) Minimum hardware requirements No information provided Windows or Linux Windows 98, 2000, and XP Publisher William H. Fletcher http://kwicfinder.com/kfNgram/kfNgramHelp.html Tom Cobb http://www.lextutor.ca/ Mike Scott http://www.lexically.net/wordsmith/index.html Support offered Brief manual provided on the software’s web site Directions provided on each screen. Contact: http://www.lextutor.ca/mailer Online manual provided on the website Target language English English and French English Target audience Beginning to advanced users Beginning to advanced users Beginning to advanced users Price Free Free License for a single user is currently around £50 (approx. US$92 or €75); a license for up to 10 users is around £250 (US$460, €376) and for up to 50 users around £500 (US$919 ,€753). Review by Omer Ari, Georgia State University OVERVIEW Three software programs--N-Gram Phrase Extractor, kfNgram, and Wordsmith Tools--are reviewed in terms of their user-friendliness and efficiency for searching for lexical bundles, which are recurring chunks of words in text. User-friendliness is defined as the ease in operating the interface of the program; efficiency is defined as fulfilling the criteria by which word combinations qualify as lexical bundles, such as frequency and multi-text occurrence (Biber, Johansson, Leech, Conrad, & Finegan, 1999; Biber, Conrad, & Cortes, 2004). Of the three software programs, N-Gram Phrase Extractor is the most user-friendly program and could be used by language teachers and learners for information on raw frequency of lexical bundles. kfNgram has an easy-to-use main interface and could also be useful to language teachers and learners. kfNgram and Wordsmith Tools additionally provide information on raw frequency and are more efficient than N-Gram Phrase Extractor. kfNgram and Wordsmith Tools could be used by researchers and others interested in multi-text occurrence as well as raw frequency information. Specific details are explained further below.Reviewed by Omer Ari Review of Three Software Programs Designed to Identify Lexical Bundles Language Learning & Technology 31 BRIEF BACKGROUND ON LEXICAL BUNDLES Corpus investigations of natural language data have resulted in major changes in the way language is viewed. Using specially developed software, researchers have discovered frequently recurring multiword lexical chunks in texts or corpora (Biber et al., 1999; Cortes, 2004; Sinclair, 1991; Stubbs & Barth, 2003), indicating that language is more repetitive than has been assumed. What is more, these chunks have been shown to vary across registers, i.e., conversation, academic prose, newspapers, fiction, etc. (Pawley & Syder, 1983; Stubbs & Barth, 2003). Although findings regarding frequency and variation have gained consensus among researchers, defining what counts as a chunk has met with broad disagreement. As a result, the field has seen a plethora of labels for chunks, such as lexical bundles (Biber et al., 1999), prefabs or lexical phrases (Nattinger & DeCarrico, 1992), formulaic sequences (Schmitt & Carter, 2004), and sentence stems (Pawley & Syder, 1983). Biber and his colleagues (1999, 2004) postulated a set of defining criteria to identify register-bound lexical bundles. Accordingly, there are two fundamental criteria for a multi-word combination to be considered as a lexical bundle: (a) it must occur frequently in a register, and (b) it must occur in multiple texts in that register. Frequency cut-off points for both criteria have usually been determined based on the researchers' goals. For example, Biber et al. (1999) set out their register-based research with a very flexible cut-off point of ten in one million words. Biber, Conrad, & Cortes(2004), however, were more conservative in their search for lexical bundles, using the criteria of 40 in one million words. Cortes (2004), on the other hand, opted to set the cut-off point in her data at 20 in one million words. The second criterion of multi-text occurrence was intended by Biber et al. (1999) to avoid idiosyncratic uses of lexical bundles by individual speakers or writers in a given register. Multi-text occurrence thus assumes that a lexical bundle is shared by other members of the discourse community who communicate in that register. Working with small corpora may make it difficult to apply this criterion due to limited availability of different texts. This criterion has largely been ignored in the search for lexical bundles, mainly because raw frequencies satisfied researchers' purposes or because researchers did not have access to large corpora. DESCRIPTION OF SOFTWARE PROGRAMS AND COMPARATIVE EVALUATION The three software programs designed to help researchers and teachers search for lexical bundles that are reviewed here are: kfNgram, a free downloadable software program; N-Gram Phrase Extractor, part of the online corpus tool Compleat Lexical Tutor; and Wordsmith Tools, a downloadable software program available for purchase. The programs are reviewed for their efficiency and user-friendliness (see Table 1). To reiterate, software efficiency is defined as a program’s capability to identify lexical bundles in running text by frequency and multi-text occurrence; and user-friendliness is defined as the ease with which the program can be used by a user who may have little experience in using computers. Table 1. The Software Programs Rated for their Ability to Perform Various Tasks kfNgram N-Gram Phrase Extractor Wordsmith Tools analyzing a long text + - + analyzing multiple texts + - + reporting frequency + + + determining multi-text occurrence + - + user-friendly + + - efficient (frequency and multi-text occurrence) + - +Reviewed by Omer Ari Review of Three Software Programs Designed to Identify Lexical Bundles Language Learning & Technology 32 kfNgram kfNgram is a user-friendly tool. After the user adds a text file into the input field, he or she has to select only the desired length of particular lexical bundles and the floor, the minimum frequency of occurrence, in the corpus or text. The search takes


Download review3
Our administrator received your request to download this document. We will send you the file to your email shortly.
Loading Unlocking...
Login

Join to view review3 and access 3M+ class-specific study document.

or
We will never post anything without your permission.
Don't have an account?
Sign Up

Join to view review3 2 2 and access 3M+ class-specific study document.

or

By creating an account you agree to our Privacy Policy and Terms Of Use

Already a member?