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Research Workshop 2: Content Analysis (lecture notes)

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Detailed lecture notes from Research Workshop 2: Content Analysis

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  • October 6, 2020
  • 22
  • 2018/2019
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Research Workshop: Content Analysis


Lecture 1: Introduction, research questions, and sampling


What is content analysis?
Content Analysis ​is a research method that can be used to analyze characteristics of registered
content of communication.

Quantitative analysis §of characteristics of media content (media messages)
● Quantitative: The analyzing occurs in a ​systematic​, ​objective​, r​ eplicable​ manner.
● Types of content: more m ​ anifest​ to more l​ atent​, but always measurable and quantifiable

“Founding Fathers” of quantitative content analysis
● Bernard Berelson (1912-1979): ​Content analysis in communication research (1952)
● Ole Holsti (1933-): C
​ ontent analysis for the social sciences and humanities (1969)
● Klaus Krippendorff (1932-): ​Content analysis: An introduction to its methodology (1980)

Content analysis is very broad and encompasses a whole lot of things.

But a lot of content analysis is about the question of ​representation​. Representation being
about things such as ethnicity, gender roles etc. To what extent and in what matter are certain
subpopulations depicted in the media? Use content analysis to measure how things are looking
in media content to then conclude if we find the dominant picture desirable.

But is can also be used by corporations for example to see how the public views a particular
brand from example.

Why content analysis?
Content is c​ entral​ to processes of communication.
● Cause of (and precondition for) media ​effects​.
● Outcome of media production and environment factors.

(1) Content analysis is (accordingly) fundamental to theory building in Communication Science.

,“Content analysis is crucial to any theory dealing with the impact or antecedents of content …
[One] cannot study mass communication without studying content … Absent knowledge of the
relevant content, all questions about the processes generating that content or the effects that
content produces are meaningless.”

(2) Data from content analysis can be linked to data from a s​ urvey
● Relevant media content is the independent variable in studies about media impact
● As a measure of exposure, content is superior to respondent self-report
● Measuring content = explicating media impact; not measuring = speculating


For example: ​Gerbner et al. developed the Mean World Index. The Mean World Index finds
that long-term exposure to television in which violence is frequent cultivates the image of a
mean and dangerous world. But without knowing how much violence there is in the media,
this theory could not be developed.


(3) Selection of analyzed media content can serve as (representative) stimulus material in
experiment​.

(4) Content analysis offers valuable insight into (and raises questions about) our ​mediated
reality​ (most of what we know about the world is thanks to the media)
● How complete, accurate, realistic is media content? → Media performance
● How does media content originate? Whose reality? → Power relations

(5) Advantages of content analysis (over other methods)
● Accessible (as to: data, cost)
● Non Obtrusive
● Non Reactive (→ control)
○ Mainly for manifest content
● Longitudinal in no time (retrospectively a time machine)

Roadmap content analysis
1. Formulate research question (hypothesis)
2. Draw a sample (usually)

, 3. Create ​codebook​ with c​ oding scheme
4. Do c​ oder training (​ using codebook)
a. Usually: adjust and refine codebook
5. Test r​ eliability of coding
6. Repeat step 4 and 5 (usually)
7. Code sampled material (collect data)
8. Analyze data (answer research question)
9. Report study

Research questions
Research questions can be more ​descriptive​ or more ​explanatory​ in nature.

Descriptive
Content analysis using descriptive research questions: d
​ escribe​ (variation in) the presence of
characteristics of media content in a given period.

Dominant in practice oriented content analyses: monitoring, trend research


For example:
● Did the number of news stories about the “automation” of jobs and professions
increase in the 2007-2017 time period?
● How was Facebook evaluated as a corporation in economic news stories of quality
and business newspapers in 2018?


Descriptive research questions in content analysis:

● Raise “why?” questions, but do not answer those
● May lead to answers that stimulate one’s curiosity
○ Why is media content like this? → Potential causes
○ What does this mean for media users? → Potential consequences
● Therefore essential as 1st phase of research program about effects of and on media
content

Explanatory
Content analysis using explanatory research questions: e ​ xplain​ variation in (a) the presence of
[characteristics of media content] in a given period or (b) [characteristics of users of media
content].

Research questions about (causal) relationships, for example between:
● 2 mutual content characteristics
● 1 content and 1 production-related characteristic
● 1 content and 1 user characteristic

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