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

Loading next page...
 
/lp/springer_journal/force-and-influence-in-content-analysis-the-production-of-new-social-jv0f7Tfq0n
Publisher
Springer Journals
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

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off