Blythe, Stuart "Coding Digital Texts and Multimedia"
From RhetorClick
| (One intermediate revision not shown) | |||
| Line 1: | Line 1: | ||
| - | In his article, Blythe discusses why he believes coding to be an important device when analyzing digital texts. | + | In his article, Blythe discusses why he believes coding to be an important device when analyzing digital texts. He breaks his argument up into two main sections: “Methods” and “Methodology.” |
| + | |||
| + | In the first section, Blythe breaks down the coding procedure step-by-step, beginning with how to choose your artifacts and finishing with how to analyze your results. Blythe explains the steps of coding in a sequential order: | ||
| + | * defining sets | ||
| + | * selecting samples | ||
| + | * defining a unit of analysis such as words, T-units, exchanges, and rhetorical units, or non-verbal cues such as facial expressions and intonation | ||
| + | * creating a set of codes | ||
| + | |||
| + | He explains that, “Essentially, analysis involves finding patterns and interesting anomalies in the coded data. To some extent, analysis may be an intuitive process based upon a researcher’s ability to find interesting trends in the data” (220). | ||
| + | |||
| + | Blythe discusses in depth the difference between manifest content, which obviously belongs to one category or another, and latent content, which is less clearly defined and could be interpreted in a variety of ways. He suggests several methods, such as scanning data before coding begins to identify latent content, to make sure coding of latent content stays consistent. | ||
| + | |||
| + | In the methodology section of his article, Blythe addresses arguments against coding and provides rebuttals. The main argument he addresses is that the individual often gets lost in data coding, where the focus is on the “big picture” (226). He discusses the ethics of critical research as it can be tied to data coding and suggests that researchers should always remember they are studying communication by human beings, not faceless research subjects. | ||
| + | |||
| + | Blythe states in his conclusion, “The key to data coding, then, is knowing what it will reveal and conceal, and to combine it with other methods in order to create a more complete picture” (226). | ||
| + | |||
| + | == Glossary Terms == | ||
| + | |||
| + | The following key terms are defined in the [[Glossary]]: comprehensive sampling, convenience sampling, criterion sampling, data coding, evidentials, latent content, manifest content, method, methodology, nonverbal units, random sampling, rhetorical units, T-units, verbal units | ||
Latest revision as of 02:36, 17 April 2012
In his article, Blythe discusses why he believes coding to be an important device when analyzing digital texts. He breaks his argument up into two main sections: “Methods” and “Methodology.”
In the first section, Blythe breaks down the coding procedure step-by-step, beginning with how to choose your artifacts and finishing with how to analyze your results. Blythe explains the steps of coding in a sequential order:
- defining sets
- selecting samples
- defining a unit of analysis such as words, T-units, exchanges, and rhetorical units, or non-verbal cues such as facial expressions and intonation
- creating a set of codes
He explains that, “Essentially, analysis involves finding patterns and interesting anomalies in the coded data. To some extent, analysis may be an intuitive process based upon a researcher’s ability to find interesting trends in the data” (220).
Blythe discusses in depth the difference between manifest content, which obviously belongs to one category or another, and latent content, which is less clearly defined and could be interpreted in a variety of ways. He suggests several methods, such as scanning data before coding begins to identify latent content, to make sure coding of latent content stays consistent.
In the methodology section of his article, Blythe addresses arguments against coding and provides rebuttals. The main argument he addresses is that the individual often gets lost in data coding, where the focus is on the “big picture” (226). He discusses the ethics of critical research as it can be tied to data coding and suggests that researchers should always remember they are studying communication by human beings, not faceless research subjects.
Blythe states in his conclusion, “The key to data coding, then, is knowing what it will reveal and conceal, and to combine it with other methods in order to create a more complete picture” (226).
Glossary Terms
The following key terms are defined in the Glossary: comprehensive sampling, convenience sampling, criterion sampling, data coding, evidentials, latent content, manifest content, method, methodology, nonverbal units, random sampling, rhetorical units, T-units, verbal units
