1. Content Analysis: An Introduction Kimberly A. Neuendorf, Ph.D. Cleveland State University Fall 2011

2. Content Analysis Defined  Content analysis is a summarizing, quantitative analysis of messages that relies on the scientific method (including attention to objectivity/intersubjectivity, a priori design, reliability, validity, generalizability, replicability, and hypothesis testing)  It is not limited as to the types of variables that may be measured, nor to the context in which the messages are created or presented [Source: Neuendorf, K. A. (2002). The content analysis guidebook. Thousand Oaks, CA: Sage Publications.]

3. Content Analysis within the Family of Empirical Methods  Experiment: At least one IV (independent variable) is manipulated; unit of data collection is often (but not always) in a controlled (e.g., laboratory) setting (if not, it may be called a field experiment)  Survey: Variables are measured as they “naturally” occur; unit of data collection is typically situated in its (his/her) natural environment; no variables are manipulated  Qualitative Methods: Includes such variants as ethnography, narratology, focus groups, and participant observation; the researcher, and their knowledge and skills, are an integral part of the measurement process

4. Content Analysis within the Family of Empirical Methods - 2 Experiments Surveys Qualitative Studies Content Analyses??

5. Content Analysis within the Family of Empirical Methods - 2 Experiments Surveys Qualitative Studies Content Analyses??

6. The Growth of Content Analaysis: Timeline—Content/Text Analysis Publications by Year

7. A “Simple” Content Analysis: Gottschall et al. (2008) ( Gottschall, Jonathan, et al. (2008). The “beauty myth” is no myth: Emphasis on male- female attractiveness in world folktales. Human Nature, 19, 174-188.)  An example of results from a fairly “easy” content analysis is shown in Figure 1.2. The figure summarizes the findings of Gottschall et al. (2008), a team of 31 co-authors/coders who inspected folktales from around the world for one particular aspect—the use of attractiveness descriptors for females (vs. males). The study included measures of— (a) attractiveness and unattractiveness references (measured via the presence of 58 pre-chosen adjectives and their variants (e.g., pretty, prettiest; ugly, uglier, ugliest)), and (b) the gender of the character to whom each reference applied (measured via personal pronoun). Additionally, (c) a rough measure of how many characters in each tale were female and male was executed via electronic word searches for pronouns, so that attractiveness references could be expressed as proportional to the number of characters of that gender.  So, just three measures were developed for this study. The coder training task was relatively simple, and acceptable intercoder reliability was achieved, even with 30 coders.

8.  Although using an elegantly simple coding scheme, the researchers chose an ambitiously large sample for its application: 90 volumes of traditional folktales from 13 regions around the world. In total, 8.17 million words in 16,541 single-spaced pages were analyzed.  Figure 1.2 shows the main findings, the female-to- male ratio of “risk” that a character will be referred to with “attractiveness” terminology. These figures take into account the rough numbers of females and males in the tales. A “Simple” Content Analysis: Gottschall et al. (2008)

9. Figure 1.2. A “Simple” Content Analysis: Gottschall et al. (2008) Female-Male Attractiveness Emphasis in World Folktales  Figure 1.2 shows the main findings, the female-to-male ratio of “risk” that a character will be referred to with “attractiveness” terminology. These figures take into account the rough numbers of females and males in the tales. Thus, we see that stories from European folktales show the greatest “gender bias”—a female character in these tales is 8.81 times more likely to be referred to as attractive/unattractive than is a male.0.5 Overall, female characters are 6.0 times more likely to be referred to with regard to attractiveness than are males. And there is no region of the world that seems to generate folktales with gender parity, or male predominance, when it comes to attractiveness references.

10.  pause