Chapter 2 - Content Analysis

8/3/2019 Chapter 2 - Content Analysis

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Contentanalysis of

visual images


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Content Analysis

} An empirical (observational) and objective

procedure

} Quantifying recorded audio visual(includingverbal) Quantitative Analysis

} Using reliable and explicitly defined

categories(values on independent variables)

}

Deals with one or more defined areas ofrepresentation, periods or types of images unlikesemiotics and psychoanalysis

Anu


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} Material analyzed visuals , verbal, graphic, oral

indeed any kind of meaningful information

} To analyze we break down into constituent parts

variables and values

} We need precise hypotheses and clearly definedconcepts

} Kinds of hypotheses is comparative

} Eg: representation of women and men in ad

explicit hypothesis here can be : women will be

depicted in fewer outdoor situations than men inbothboth kindskinds ofof magazinesmagazines


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Values

} Elements under variables with same logic

} Elements could be substituted for each other belong to the same class

} Values each should be mutually exclusiveand exhaustive

} Exclusive any observed element ofrepresentation can onlyonly be classified into one

value on each variable} Exhaustive value should cover all the

possible categorizations on the respectivevariable


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Variables

Values

GenderGender RoleRole SettingSetting SizeSize

Male House duties Domestic Full Page

Nurse

Female BusinessExecutives

Public Half full page

Flight

attendant

More than half

page

Teacher Double page

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Quantitative results: Comparisons

& Cross - tabulations

} Content analysis classifies extensive fields of

representation in quantitative terms.

The kind of hypotheses which such quantificationhelps to test are those which compare one fieldof representation with another

example : comparisons between mens andwomens magazine advertisements in terms of

visual representations of gender roles. The table was originally published with relevant

comparison tables showing how other television

channels prioritized their respective agendas

during the same period.

Riaz


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Groups of males or females have been analyzed

according to the visual modality.

Modality here refers to the truth value or credibility

of statements about the world.

(Kress and van Leeuwen 1996 ) these authors point

out that visual images also represent people, places

and things as though they are real.. Or they areimaginings, fantasies etc.

Males are more likely than females to be shown in

factual style advertisements.

Most magazine advertisements adopt a standard

modality.


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RELIABILITY

Reliability refer to the degree of consistency shown byone or more coders in classifying content according todefined values on specific variables.

Reliability can be demonstrated by assessing the

correlation between judgments of the same sample of

relevant items made by different coders or by one coderon different occasions

Reliability is a simple but important concept. It can be

thought of measuring any quality does not yield thesame value each time it is applied to a given object,

then it is not literally a tool in the physical sense, it is amethod of classification and quantification, so its

definitions must be precise enough to be used reliably.


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To achieve high levels of reliability :

Define the variables and values clearly and

precisely and ensure that all coders understandthese definitions in the same way.

Train the coders in applying the defined criteria foreach variable and value.


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Per cent agreement

Simply calculate how frequently two coders agree theirjudgements,ensuring that they both tested on the samelarge number of items.

The researcher might choose not to employ the most

aberrant coder in the next stages of the research project,so that the average reliability was higher however the

level of reliability is below what is usually recommended0.9 or 90 %. With 4 coders, such an index is rather artificial.

It assumes that one coder is the norm and averages the

others respective agreement with this norm.


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Two technical point

A high frequency of items classified as miscellaneous

or other will spuriously inflate the apparent level ofreliability. Less than ten per cent of iteams should fallinto this category on any variable. Second

The fewer values there are on a given variable, themore likely there is to be agreement between coders

which is based on chance rather then on similarjudgement according to the definition. So binary ortripartite classifications would need to be close to 100per cent reliable.


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More sensitive measure of reliability

The index the fact that two codes may agree in their judgments purely by chance a better index hasbecome more widely used.

Scott 1955 he has proposed one of several more subtle

formulae for assessing reliability by taking account ofchance agreements based on the number of valuesdistinguished in a given content analysis : pi

pi =(per cent observed agreement)- (per cent

expected agreement.

The researcher can state the expected percentage forall values on all variables in advance of the codersjudgments being made.


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If two coders classifying a sample of 100images depicting occupational roles in

advertisements, for instance agreed on 95 % ofcases then the reliability index would be (0.95-0.205)/(1.00-0.205) = 0.94 the pi value).

A pi value of at least 0.80 should be obtained.

If this is not achieved in a pilot trial, theresearcher should re-train coders and / orredefine values and re-test the degree ofreliability.


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Limitation and Extension

The main limitation of quantitative content analysisconcern the relatively un-theorized concept ofmessages, texts or manifest content that it claims toanalyze objectively and then to quantify.

The categories of visual 'content which are mostfrequently quantified in media research arise fromcommonsense social categories such a roles depicted'settings shown, gender and age of representedparticipants in images.

Such variables are not defined within any particulartheoretical context which analyses visual semiotic

dimensions of texts That is, the framing, visual 'angles', scale of

photographic 'shot', and so on, that are part of thediscourse of visual analysis are Seldom incorporated intocontent analysis


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VALIDITY : GOING BEYONDTHEDATA

To conduct a content analysis is to try to describe salientaspects of how a group of texts represents some kinds ofpeople ,processes, events, and/or interrelationshipsbetween or amongst these.

However, the explicit definition and quantification thatcontent analysis involves are no guarantee, in themselves,that one can make valid inferences from the data yieldedby such an empirical procedure .

any form of visual analysis, is the degree to which the

resulting statements about the field analysed can be saidto describe features that are, in fact, semanticallysignificant for viewers/spectators/'readers of the images.


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The criticism that is most frequently leveled against

content analysis is that the variables/values defined aresomehow only spuriously objective.

It is claimed that they are as subjective as any semanticvariables despite being 'measured or at least counted.

However, such a criticism can be turned around, to point

to the fact that not only content analysis but all visual orverbal semiotics formal and informal, are only as valid asthe explicitness and reliability of their respectivetheoretical concepts.

Content analysis by itself, does not demonstrate howviewers understand or value what they see or hear. Still,

content analysis shows what is given priority or salienceand what is not. It can show which images areconnected with which, who is given publicity and how, aswell as which agendas are 'run by particular media.


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} Validity refers to the concept of how well a system

of analysis actually measures what it purports tomeasure. Valid inferences from a particular content

analysis, given this definition, will reflect the Degreeof reliability in the coding procedures, the

precision and clarity of definitions adopted and theadequacy of the theoretical concepts on which

the coding criteria are based. Validity refers to the

confidence one can have in the results showingthat the stated theoretical concepts offer adiscriminating description of the field being

analyzed.


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As we have seen, Content analysis provides a quantifieddimensional description of fields of representation .Themethodology can be used to provide a background mapof a domain of visual representation. Having conducted a

content analysis the researcher can then interpret theimages or the imagery in qualitative ways.

Typical or salient examples can be further analyzed to fillout the qualitative description of 'what the data mean'.So, having shown how frequently and in what contexts,

say, images of passive females occur, a Researcher mightdiscuss the psychoanalytic or ideological significance ofthe images in terms of metaphors, photographic style,historical or social context .

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Eg : Testing Semiotic Hypothesis} Images carry connotations and invite individual

reminiscence

} Experiential possibilities cannot be defined and

quantified reliably} Yet dimensions of interactiveinteractive ( how viewer is invited

to relate to an image) and of textualtextual meaning(how images are formed or balanced) can bedefined and their frequency counted

} Manifested content of images through content

analysis dissects and counts unambiguouslydefinable aspects can be quantified

} Involves empirical (observational) methodology

} Specified variables and values used to codebased on partial / small scale content analysis

Kevin


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Need of partial or small scalecontent - Analysis

1. Comparative hypothesis can be formulatedand tested using reliable categories relating

to the semiotics of visual images

2. Content Analysis can be given by precisedefinition to theoretical concepts(heresemiotics)

3. Objective criteria (unambiguouslyunambiguously) to bespecified for categorizing visual material.


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Partial content Analysis :Social Science format

1. Hypothesis

2. Procedure or method3. Results and Discussions


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Jun 2010 July 2010 Aug 2010 Sep 2010

Oct 2010 Nov 2010 Dec 2010 Jan 2011


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1. Hypotheses

} None of the models are in intimate distance

} Models on the cover pages of Jan 2010, Aug 2010,

Sep 2010, Nov 2010 seems to be in far personal

distance

} Models on the cover pages of Dec 2010 and

January 2011 seems to be in far personal distance

} Modality of the images seems to be high

} All the models seems to have almost same age

} Model on the cover page of July 2010 seems to bein close social distance

} In few models seems to cover the logo / title of themagazine


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2.Procedure / method

Variable values1. Social Distance 1.1 intimate

1.2 close personal

1.3 far personal

1.4 close social

1.5 far social

1.6 public

2.1 high

2.2 medium

2.3 low

3.1 offer- ideal (looking away from viewer)

3.2 demand/affiliation (equality) (looks at viewer,

directly, smiling)3.3 Demand/submission(looks down at viewer, mot

smiling)3.4 Demand / seduction (looks at viewer, head

canted, smiling or pouting)

3.5 others

2.Modality

3. Behavior


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3. Results and Analysis

1.Social Distance 1.1

1.21.3

1.41.5

1.6

14

21

2.Modality 2.1

2.22.3

8

3. Behavior 3.1

3.23.33.43.5

134


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4. Discussion

} The occlusion / or covering the title of themagazine happens in almost random manner. Itclearly covers the title on Jan 2010, July 2010, Sep2010, Oct 2010, Jan 2011editions showing its arandom pick rather than a shift itself.

} The visuals are put in a very constructed andbeyond the reality with studio lighting and themodels seems to be more perfect than normalpeople(reality)

} The poses of models other than the one in Jan2010 seems to have powerless poses and

increases the tenderness in women making theviewer having more power on them. Thesewomen images of almost same age or in sameage group(20-30) shows that the magazine aimsat young people especially youth and women(target audience)

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Chapter 2 - Content Analysis