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Content analysis

Content analysis. Cornel Ban. Bottom line. Turning text into numbers. e.g. Advantages. Gives way to both quantitative and qualitative operations V aluable insights over time Provides insight into complex models of human thought and language use. Disadvantages. time consuming

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Content analysis

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  1. Content analysis • Cornel Ban

  2. Bottom line • Turning text into numbers

  3. e.g.

  4. Advantages • Gives way to both quantitative and qualitative operations • Valuable insights over time • Provides insight into complex models of human thought and language use

  5. Disadvantages • time consuming • inherently reductive, particularly when dealing with complex texts • often disregards the context that produced the text

  6. Stages of CA • Main stages1. Defining the unit of analysis 2. Specifying variables and categories 3. Frequency, direction and intensity

  7. Use in IR • Identify the intentions, focus or communication trends of an individual, group or institution

  8. Steps • Identify the research questions • Choose samples. • Develop code book • Run it on 10 percent of the samples • Recalibrate • Run final codebook • Analyze the results

  9. Types • Systematic • Samples • Example of a sampling strategy • To facilitate working with a manageable data set, I employed several different randomizations to identify a sample of 126 postings (~1% of the total). First, I created a database of ~4% of all samples by creating entries corresponding to every 33rd post. Of these set, roughly every 3rd post was examined for its content. Posts that represented part of a series or had less than four characters were excluded, and the closest post in theset(33 posts before or after it) would replace it. Four posts were substituted in this manner. On average, I coded roughly every 110th article.

  10. Issues to address • reliability : coders consistently recode the same data in the same way over a period of time; • “We performed code reliability checks on 60% of the codes. Each researcher independently classified each post according to the role and category of appeal consistent with the criteria agreed in the coding sheet. Upon comparison, code reliability was 92%.” • reproducibility: coders classify categories in the same way;

  11. Use multiple classifiers • "communist” ="red,” "pinkos," "godless infidels” "Marxist sympathizers."

  12. Coding sheet

  13. Results

  14. 19. Social welfare 19.1 RIGHT: Individual responsible for own welfare – it is not the state’s/ the EU’s duty to take responsibility for individual welfare • without qualifications b. with qualifications Indicate: …………………………………………………….. 19.2 LEFT: State institutions have a responsibility to aid the weaker in society to take measures to deal with social inequalities • Without qualifications b. with qualifications Indicate: ................................................................... 19.3 Ambivalent 19.4 No evaluation

  15. Software • Dedoose software: compatibility with Mac computers, its price, and its pricing schedule. • the availability of video tutorials, online support via a web forum, and users having to only pay for services per month that the software is used. • Concordance or QSRNVivo

  16. Dedoose coding

  17. Dedoose visualization

  18. Coding interview transcripts • 1) Copy and read through the transcript - make brief notes in the margin when interesting or relevant information is found • 2) Go through the notes made in the margins and list the different types of information found • 3) Read through the list and categorise each item in a way that offers a description of what it is about • 4) Identify whether or not the categories can be linked any way and list them as major categories (or themes) and / or minor categories (or themes) • 5) Compare and contrast the various major and minor categories

  19. Coding interview transcripts • 6) If there is more than one transcript, repeat the first five stages again for each transcript • 7) When you have done the above with all of the transcripts, collect all of the categories or themes and examine each in detail and consider if it fits and its relevance • 8) Once all the transcript data is categorised into minor and major categories/themes, review in order to ensure that the information is categorised as it should be. • 9) Review all of the categories and ascertain whether some categories can be merged or if some need to them be sub-categorised • 10) Return to the original transcripts and ensure that all the information that needs to be categorised has been so. • The process of content analysis is lengthy and may require the researcher to go over and over the data to ensure they have done a thorough job of analysis

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