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Unit 12: Content Analysis
development of artificial intelligence (Colorado State University, 2004). Furthermore, it suits cross- Notes
disciplinary research, a practice that is increasingly popular (Ryan & Bernard, 2000).
As Busha and Harter (1980) explain, use of content analyses in the post-World War II information
sphere often concentrated on the interpretation of novels, such as Harvey’s 1953 “The content
characteristics of best-selling novels”. More recently, job advertisements are the favoured source
material, like in the work of Clyde (2002) and Pember (2003). This expansion of undertakings
represents some progress in LIS thinking about the tool.
And content analysis has been applied and well-received in studies all over the world. Evidence of
global LIS implementation include Leif Kajbergs (a Danish consultant to the Royal School of Library
and Information Science) review of research and development publications on technology and
competence in 1992, Maxine Rochesters (1995b) scrutiny of professional communication in Australian
library and information science through journal articles, and William Moens 1997 examination of
the metadata of United States government records.
Content analysis has been dismissed due to its large demands of labour, time and funds (Ellis, 1993;
Powell, 1997), yet this flaw exists in numerous research methods. Busha and Harters (1980)
identification of the disadvantage that no single model is applicable, and each new analysis must be
structured according to the accomplishment of a specific task is undeniable. However, as List (2003)
suggests, existing frames from similar content analysis studies can be modified. Furthermore,
technological aid is available for the numeric tasks, via standard spreadsheet applications (like
Excel) or specifically formulated content analysis packages (such as Textpack).
Content analysis is also frequently dismissed due to the perceived weakness of subjectivity. Again,
this issue affects all qualitative research. Validity does depend upon the collective opinion of coders,
but this is managed by checking the level of agreement with a correction formula (theory trailblazer
Krippendorf set a benchmark of 0.70). The warning that items that are not coded do not receive
attention, and hence the study may miss something of significance (Ellis, 1993), is rebutted by pointing
out that methodology selection involves consideration of tool appropriateness.
Reluctance of researchers to incorporate this tool arises from habit—as Rochester (1995a) remarked,
In Australia the survey seems to be regarded as a standard strategy for all library and information
science problems . Additionally, research in our sphere is often a case study conducted by an
employee focusing on their organization. Low usage of content analysis may be attributed to it
being unfairly maligned. It is suggested that much of its poor reputation stems from past studies of
poor quality, where researcher error (a possibility in any technique) led to tenuous conclusions.
Wider publicity of the merits of the research method of content analysis in Library and Information
Studies would greatly benefit the field. The criticisms of potential difficulties of the tool are un-
founded, and studies in which content analysis has been applied have subsequently added to the
LIS body of knowledge. I hope that once content analysis is better understood it will be better
utilised.
Content Analysis: Examples
The Palmquist, Carley and Dale study, a summary of “Applications of Computer-Aided Text
Analysis: Analyzing Literary and Non-Literary Texts” (1997) is an example of two studies that have
been conducted using both conceptual and relational analysis. The Problematic Text for Content
Analysis shows the differences in results obtained by a conceptual and a relational approach to a
study.
The Palmquist, Carley and Dale Study
Consider these two questions: How has the depiction of robots changed over more than a century
worth of writing? And, do students and writing instructors share the same terms for describing the
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