Lecture 1

Question 1

What is content analysis?

Answer 1

A research method to analyse characteristics of registered content of communication (written, verbal and visual)

Question 2

Quantitative analysis of content characteristics of media messages

Answer 2

Analysing is systematic (pre agreed rules), objective and replicable
Content characteristics: manifest to latent, but always measurable and quantifiable

Question 3

What is CA?

Answer 3

Huge. Visibility, bias, dangerous, news frames, health news, social media, movie series, content for children

Question 4

WHY content analysis?

Answer 4

Content analysis fundamental to theory building in Communication Science.

Question 5

Content is central to processes of communication

Cause of - and precondition for - media effects

Outcome of characteristics - and surrounding - media producers
> Makes possible testing relationships throughout the entire process of communication

Answer 5

Centrality model:

• Antecedent conditions
• Media content
• Media effects

Question 6

WHY (1)

Answer 6

Content analysis is crucial to any theory dealing with impact or antecedents of content

In the long run one cannot study mass communication without studying content

Absent knowledge of the relevant content, all questions about the processes generating the content or the effect that content produces - are meaningless.

Question 7

WHY (2)

Answer 7

Content analysis can help strengthen designs of media effects research:

Data from content can be linked to data from survey to explain media effects
Relevant media content is the IV in media impact
As a measure (of opportunity to) exposure, content is superior to respondent self-report.

Measuring content = explicating media impact,

Not measuring: speculation.
Selected analysed messages can serve as realistic (representative) stimulus material in experiment

Findings will have higher ecological validity

Question 8

WHY (3)

Answer 8

Offers insights and raises questions about our mediated reality

How accurate, complete, realistic is media content?

> Media performance (media bias) (normative)
How does media content originate? Whose reality? (outcome, and who owns the me

> Power relations - those with power can control better than those with little power.

Question 9

WHY (4)

Answer 9

Content analysis has clear practical advantages:

Accessible:
Easy access to media and messages

Low cost
Media messages always consent

Question 10

UNOBTRUSIVE -> nonreactive (not interfering anything - in survey we do)

Answer 10

Media messages never react (we are not bothering them)

Longitudinal in no time - retrospectively a time machine (go back decades, archives).

Question 11

Doing CA (with human coders)

Answer 11

RQ and hypo
Design measures, code book etc
Train coders (refine codebook)
Pre-test reliability of coding
Repeat steps 3-4
Draw samples and reliability tests
Code sampled media messages
Formally test reliability of coding
Analyse study data
Report study

Question 12

Research questions

Answer 12

Descriptive RQ: questions about media content only. In isolation of its production (causes) or consumption (effects)

Answers describe (variation in) media content in some period

Value of description in scientific content analysis

Media content may be assessed against some normative standard

Essential as 1st (explorative) phase of broader research program

• Normative standards:
  Descriptive RQ: example: Are Whites overrepresented as victims?

Question 13

Three steps process (media content)

Answer 13

Explore new research territory by analysing meaning or potential causes and or effects of analysed media content

Make reasoned inferences from results about meaning or potential causes and or effects of analysed media content

Test (causal) relationships with media content as cause or outcome in future research

Question 14

Explanatory research questions:

Answer 14

Questions linking media content to suspected cause or consequence of that content

Content posited as explanation (cause) or as itself being explainable (outcome)

Question 15

Content-as-cause: to what extent does variation in media explain variation in media consumer reactions to this content?

Content-as-outcome: to what extent is variation in media itself explained by variation in characteristics of our surrounding - the producers of this content?

Answer 15

Media content as outcome or cause

Media producer characteristics → media content characteristics → media consumer characteristics

Question 16

Comparative questions

Answer 16

Compare different populations of messages of media content
Answers describe differences in content between the message populations compared

Question 17

Comparing media categories

Answer 17

Media worker - micro level: categories an individual characteristics of media workers directly responsible for producing media (male female, white non white etc)

Media organisation categories - meso level: categories of characteristic of the company in which media workers operate (public private, left liberal or conservative)

Media environment categories - macro level: categories of characteristics of the broader geographical environment in which media organisations operate.

((macro-level comparisons are often cross-national). (individualist collectivist, high vs low media regulation))

Question 18

Time categories

Answer 18

Before and after an intervention
Historically distinct eras

Question 19

Comparing theme categories

Answer 19

Theme related events (what was the framing - terrorism or act of violence)
Context different but type of event same

Question 20

Value of comparison in scientific content analysis

Answer 20

Allows for testing relationship between a message population variable and message content variable

Essential for theory building concerning effects on media content

Often cannot isolate true causes of observed differences in content but does allude to hint at these causes

Facilitates making reasoned inferences about causes of content: why these observed differences between these message populations?

Question 21

Description: less theoretical, less knowledge gain, less scientific (has real value)

Answer 21

Explanation: more theoretical, more knowledge gain, more scientific

Question 22

Population (universe): all units about which a CA wants to make a claim

Answer 22

Census: All units in the population are analysed
Often impossible
Unnecessary if sample is representative

Question 23

Probability samples: purely by chance, each member equal chance (full overview of population → sampling frame)

Answer 23

Sampling frame: list with all numbered units in population available for selection

Question 24

Prob sample: in principle representative

Answer 24

Representative: a relevant characteristic of media content in the sample distributed in same way as population

Pre-condition: for generalising from sample to population (external validity)

Question 25

Non-prob sampling - samples created by choice - researchers chooses units

Answer 25

Convenience sample:

Chosen messages were directly available
Choices based on practical considerations

Purposive sample:

Chosen messages were considered meaningful to the study
Choices based on substantive considerations
(like a magazine or something)

Question 26

Consecutive unit sample:

> Suitable if analysing continuing event or story in specific period - makes possible analysing evolution of story

Not suitable for longer periods
Risk: missing large variation in content over time

Especially with news: unpredictable and diverse

Answer 26

All relevant messages published in a chosen time period

Time period: uninterrupted series of time units
Common version of time purposive sample

Question 27

Simple random sampling: chance based sampling of n units from sampling frame

Answer 27

Not always effective:
No control over dispersion spread of selected units across sampling frame

Risk: selection bias (under or over representation across time)
Problematic for small samples, from long periods

Sample from long period needs to be large to be representative

Question 28

Systematic sampling:

Answer 28

Drawing every unit from sampling frame following randomly determined starting point
N is skip interval, depends on desired sample size

Main advantage: control over dispersion over units selected from sampling frame

Even dispersion (across time)

Highly recommended for small samples, samples from long periods

Question 29

Stratified sampling

Answer 29

Subpopulations based on characteristics meaningful

Often: stratify units by some media category (source) or time unit

Often: share of each stratum in sample proportion to size of stratum in population

Recommend: population that is diverse.
Ensure sample reflects full range of content present in population across media landscape

Question 30

Stratify by media category:

Answer 30

List of all songs on top 10 over 19 months

Stratified according to genre: pop, hiphop, etc (sampling frames)

Each genre equally: simple random sample of 50 songs from each genre’s sampling frame

Question 31

2 common sampling problems to overcome:

Answer 31

All prob techniques require a sampling frame.

The units to sample are not identical to unit in analysis

Cause: Lots of content is offered in clusters.

Question 32

2 dimensions of clustering:

Answer 32

Spatial dimension: media channels or productions

Television news - cluster of news stories.

Netflix - cluster of episodes. Influencer - cluster of posts.

Question 33

Temporal dimension: time units

Answer 33

Edition (publication date): custer of news stories
Season: cluster of episodes

Question 34

Units of analysis:

Answer 34

About which the study makes a claim (RQ)

Answer 35

Sampling units: units randomly selected per step of the sampling process for inclusion in the sample: multiple steps=multiple types of sampling units.

Question 36

Sampling units: 1. Titles, 2. Publication dates, 3. Stories about the UK general election

Question 37

Multistage sample

Answer 37

Sample created through multiple rounds of sampling

First stages: stratified or cluster along spatial and temporal dimensions of media content

Recommended if sample should reflect multiple dimensions of content

Titles often not random but purposive
Editions often random using constructed period sampling

Question 38

Constructed period sampling: probability sampling of time units

Answer 38

Ensures equal representation of selected time units across research

All time units (days of week) are even
Recommended for analysis of periodical media over long periods

Periodical media: regular intervals

Question 39

WHY

Answer 39

The rhythm and logic of periodical media cause systematic and predictable variation repeating patterns in content: cyclical variation

If ignored: selection bias

Constructed period sampling eliminates such bias

Effective and efficient: representative but not large

Question 40

Systematic version:

Answer 40

Skip interval chosen in such way that all publication are represented

7 days + 1 day to create 3 constructed weeks over 6 months

Even temporal dispersion of each publication
3 constructed weeks: each day of week selected 3 times - equal representation

Question 41

Stratified version

Answer 41

Entire period divided into time strata: for each stratum: a sampling frame from which to sample

Example: time strata; all days of the week → 7 sampling frames

2 constructed weeks: random two mondays, two tuesdays etc

Question 42

Nexis uni and probability sampling:

Answer 42

Advantages: many relevant articles quickly
Easy to create a sampling frame listing all relevant articles from random sample (clusters are circumvented)

Question 43

Disadvantages: Search phrases have flaws

Answer 43

Subjective choice by researcher

Possibly not optimised enough of identifying all and only relevant articles
Completeness of database is questionable
Some key titles not available, relevant articles not available, visual content not archived.

Question 44

Nexis uni and prob sample

Answer 44

Does a sampling frame offer a full overview?
Does each article from the population have an equal chance? Questionable.
Certainty not…