Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/761
Title: Type/Token-Taken informetrics
Authors: EGGHE, Leo 
Issue Date: 2003
Publisher: Wiley
Source: Journal of the American Society for Information Science and Technology, 54(7). p. 603-610
Abstract: Type/Token-Taken informetrics is a new part of informetrics that studies the use of items rather than the items itself. Here, items are the objects that are produced by the sources (e.g., journals producing articles, authors producing papers, etc.). In linguistics a source is also called a type (e.g., a word), and an item a token (e.g., the use of words in texts). In informetrics, types that occur often, for example, in a database will also be requested often, for example, in information retrieval. The relative use of these occurrences will be higher than their relative occurrences itself; hence, the name Type/Token-Taken informetrics. This article studies the frequency distribution of Type/Token-Taken informetrics, starting from the one of Type/Token informetrics (i.e., source-item relationships). We are also studying the average number * of item uses in Type/Token-Taken informetrics and compare this with the classical average number in Type/Token informetrics. We show that * always, and that * is an increasing function of . A method is presented to actually calculate * from , and a given , which is the exponent in Lotka's frequency distribution of Type/Token informetrics. We leave open the problem of developing non-Lotkaian Type/Token-Taken informetrics.
Document URI: http://hdl.handle.net/1942/761
ISSN: 1532-2882
DOI: 10.1002/asi.10247
ISI #: 000182425300002
Category: A1
Type: Journal Contribution
Validations: ecoom 2004
Appears in Collections:Research publications

Files in This Item:
File Description SizeFormat 
Type token.PDFNon Peer-reviewed author version354.59 kBAdobe PDFView/Open
type 1.pdf
  Restricted Access
Published version83.48 kBAdobe PDFView/Open    Request a copy
Show full item record

SCOPUSTM   
Citations

10
checked on Sep 2, 2020

WEB OF SCIENCETM
Citations

11
checked on Apr 30, 2024

Page view(s)

54
checked on Sep 7, 2022

Download(s)

212
checked on Sep 7, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.