“Content Analysis: Counting What You (Think You) See”

Research Question: What activities do 12-18 year old readers engage in?

I am choosing to utilize the content analysis in response to this picture because the other happenin’ side of my degree utilizes amazing cataloging (or what Rose refers to as ‘coding’) skills. While this may seem like a simple analysis, in retrospect, it is a bit more difficult than it seems. Rose mentions the coding categories on page 60, stating that the utilized in analyzing the images must be:

* exhaustive

* exclusive

&

* enlightening

Further they must be valid (connect between text, context, and code) and replicable (clearly defined so that researches at different times and places would be able to code the image in exactly the same way). Engaging each of these factors when analyzing a picture can be difficult, especially when one is using the codes for the purpose of cateloging an image within a library collection.

The reason I chose this picture is because my Photoshop image was definitely more feminine. Although, this picture has a girl in it… so… well, yeah, that would attract 12-18 year old boys, right?

4 Steps to Content Analysis

Step 1: Find Your Image CHECK!

(Note: Rose discusses the idea of analyzing multiple images. In order to do so, the images must be representative and significant. In order to ensure those two qualities, sampling strategies might include random, stratified, systematic, and cluster. Which ever one is chosen will depend on the research question: What activities do 12-18 year old male readers engage in?).

Step 2: Devising your categories for coding.

While I am currently only working with one image, I am able to imagine some codes based on further pictures which might be put into this selection. Also, I would need to be sure to include codes which speak to my research question.

That said… here are some c-c-codes based on this list provided on pages 60-61:

1. in front of picture (location)

2. woman and picture (unit of article organization)

3. no smile (smiling in the photograph)

4. women (gender of adults depicted)

5. 20-30 (age of those depicted): although, if I wanted to market this for my 12-18 year old audience could I fib on the age??? Hmmm??

6. walking briskly (aggressive activity)

7. no action (activity level of main foreground figures)

8. standing and looking (activity type of main foreground figures)

9. looking left (camera gaze of main person photographed)

10. drawing behind (surroundings of people photographed)

11. one (group size)

12. middle class, paints with stain, artist (wealth indicators in photograph)

13. white (skin color)

14. casual, paints with stain (dress style)

15. straight on (point from which camera perceives main figures).

Other codes which I might choose to include: color of photograph, body position, time of day… etc. Of course, if I were actually cataloging this picture, I would also include information about the picture such as the artist. However, because content analysis is simply about the ‘composition modality’, it does not leave room for discussion of artist or symbolism.

Step 3: Coding the images

In reviewing the above information, the codes of the image would be that which is not in the parentheses. It is those codes that must be replicable. It is also this stage which is the most difficult because a cataloger must not only focus on making the codes replicable for fellow catalogers, but must also take into consideration users who have had little to no library search and retrieve training. And, again, if I were trying to have a 12-18 year old reader access this image, I would need to take into consideration their jargon and vocabulary. What I may see as a female standing and looking at a picture of a walking female, they may see as something abstract and aloof and search for those terms (although, in an ideal cataloging world the abstract would be categorized right along with the un-abstract or, uh, ‘literal’ as it were).

Step 4: Analyzing the Results

This is where, if I were to have a group of images, I would apply the statistical information based on the number of pictures which were categorized into each code. In considering my research question, an important code might be age. If I were to hope that a 12-18 year old would view this image, then the age of the woman in the picture might be a bit high. If any of my readers are artists they might be interested in looking at other photographs with pictures in them. As a cataloger, I would ensure that all of these categories and topics connect. Although, again, I would have to make sure that they were valid. If this was the only picture that had an older woman in it, it would probably not be ethically wise to lie about the woman’s age, as suggested earlier! (Shame on me!) 😉 To reach teens, perhaps I could use a word like ‘mentor’, although that term does not speak to replicability necessarily.

Whew! This content analysis stuff really is a tough cookie!

But, you maybe asking, “Is content analysis a critical visual methodology?” Well… yes… because it’s in the book! And, because if it wasn’t catalogers wouldn’t need a master’s degree in the field of library science. But maybe Rose can say it more eloquently, “Clearly, every stage of content analysis, from formulating the research question, to developing coding categories, to interpreting the results, entails decisions about meaning and significance… Lutz and Collins suggest that, especially if the coding of images is carefully formulated, content analysis can be used to interpret the cultural meaning of images” (66).

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