White HD, Combining bibliometrics, information retrieval, and relevance theory, Part 2: Some implications for information science, JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY 58 (4): 583-605 FEB 15 2007

[Eugene Garfield]

E-mail Addresses: whitehd at drexel.edu 

Title: Combining bibliometrics, information retrieval, and relevance 
theory, Part 2: Some implications for information science 

Author(s): White HD (White, Howard D.)
 
Source: JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND 
TECHNOLOGY 58 (4): 583-605 FEB 15 2007 

Document Type: Review 

Language: English 

Cited References: 110      Times Cited: 0 
       
Abstract: When bibliometric data are converted to term frequency (tf) and 
inverse document frequency (idf) values, plotted as pennant diagrams, and 
interpreted according to Sperber and Wilson's relevance theory (RT), the 
results evoke major variables of information science (IS). These include 
topicality, in the sense of intercohesion and intercoherence among texts; 
cognitive effects of texts in response to people's questions; people's 
levels of expertise as a precondition for cognitive effects; processing 
effort as textual or other messages are received; specificity of terms as 
it affects processing effort; relevance, defined in RT as the 
effects/effort ratio; and authority of texts and their authors. While such 
concerns figure automatically in dialogues between people, they become 
problematic when people create or use or judge literature-based 
information systems. The difficulty of achieving worthwhile cognitive 
effects and acceptable processing effort in human-system dialogues 
explains why relevance is the central concern of IS. Moreover, since 
relevant communication with both systems and unfamiliar people is 
uncertain, speakers tend to seek cognitive effects that cost them the 
least effort. Yet hearers need greater effort, often greater specificity, 
from speakers if their responses are to be highly relevant in their turn. 
This theme of mismatch manifests itself in vague reference questions, 
underdeveloped online searches, uncreative judging in retrieval evaluation 
trials, and perfunctory indexing. Another effect of least effort is a bias 
toward topical relevance over other kinds. RT can explain these outcomes 
as well as more adaptive ones. Pennant diagrams, applied here to a 
literature search and a Bradford-style journal analysis, can model them. 
Given RT and the right context, bibliometrics may predict psychometrics. 

Addresses: White HD (reprint author), Drexel Univ, Coll Informat Sci & 
Technol, Philadelphia, PA 19104 USA
Drexel Univ, Coll Informat Sci & Technol, Philadelphia, PA 19104 USA

E-mail Addresses: whitehd at drexel.edu
 
Publisher: JOHN WILEY & SONS INC, 111 RIVER ST, HOBOKEN, NJ 07030 USA 

Subject Category: Computer Science, Information Systems; Information 
Science & Library Science 

ISSN: 1532-2882 

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