Force and Influence in Content Analysis: The Production of New Social Knowledge

Force and Influence in Content Analysis: The Production of New Social Knowledge We examine the two traditions of content analysis: the first in which one substitutes words of a text with categories, and the second in which one looks for clusters of words that may refer to a theme. In the first tradition, preexisting dictionary categories give meaning to the words; in the second, meaning comes after the fact. Preexisting dictionary categories (the substitution model) are calibrated instruments applied within experimental designs that leave no space for doubt; meanwhile, the ability of the correlational model to conjure up complex themes from fragments of a text yields no unique solution. These differences have bearings on the production of new social knowledge. We expound on the epistemological foundations of the two traditions of interpretation and draw from them decision rules upon which one may rely for choosing among appropriate content-analytic tactics. Two reasons make this essay timely and critical: (1) the increasing variety of new content-analyticsoftware for particular purposes and (2) the almost exclusive focusing on software and technology at the expense of adjusting the choice of the software to the nature of the text. Two studies, one in historiometry, the other in autobiography, illustrate the liabilities and benefits of the two models of content analysis. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quality & Quantity Springer Journals

Force and Influence in Content Analysis: The Production of New Social Knowledge

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Publisher
Kluwer Academic Publishers
Copyright
Copyright © 2003 by Kluwer Academic Publishers
Subject
Social Sciences; Methodology of the Social Sciences; Social Sciences, general
ISSN
0033-5177
eISSN
1573-7845
D.O.I.
10.1023/A:1024401325472
Publisher site
See Article on Publisher Site

Abstract

We examine the two traditions of content analysis: the first in which one substitutes words of a text with categories, and the second in which one looks for clusters of words that may refer to a theme. In the first tradition, preexisting dictionary categories give meaning to the words; in the second, meaning comes after the fact. Preexisting dictionary categories (the substitution model) are calibrated instruments applied within experimental designs that leave no space for doubt; meanwhile, the ability of the correlational model to conjure up complex themes from fragments of a text yields no unique solution. These differences have bearings on the production of new social knowledge. We expound on the epistemological foundations of the two traditions of interpretation and draw from them decision rules upon which one may rely for choosing among appropriate content-analytic tactics. Two reasons make this essay timely and critical: (1) the increasing variety of new content-analyticsoftware for particular purposes and (2) the almost exclusive focusing on software and technology at the expense of adjusting the choice of the software to the nature of the text. Two studies, one in historiometry, the other in autobiography, illustrate the liabilities and benefits of the two models of content analysis.

Journal

Quality & QuantitySpringer Journals

Published: Oct 17, 2004

References

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