Quantitative Research Methodology SOC 509

Quantitative Research Methodology SOC 509. Lesson 21: Quantitative Content Analysis.

Introduction. Content analysis refers to a family of procedures for the systematic, replicable analysis of text. In essence it involves the classification of parts of a text through the application of a structured, systematic coding scheme from which conclusions can be drawn about the message content. By clearly specifying the coding and other procedures content analysis is replicable in the sense that other researchers could reproduce the study..

Content analysis can be carried out quantitatively but also qualitatively. In this lecture, we focus on quantitative content analysis. Content analysis can be applied to all kinds of written text such as speeches, letters or articles whether digital or in print, as well as text in the form of pictures, video, film or other visual media. It can be used to examine both the manifest and the latent content of a text. Manifest content refers to the visible, countable components of the message. Latent content refers to the meaning that may lie behind the manifest content..

Manifest content in the form of images of women in advertisements engaged in activities such as domestic work or child care, for example, might be taken as indicators of gender stereotyping, a latent concept. Both manifest Content analysis can also be used to investigate both substantive (content) and form (or formal) features of a text. Substantive features refer to what is being said in the message. Form features refer to how it is being said ( Schreier 2012). A content analysis of advertisements, for instance, might distinguish between the way in which the benefits of a product are described (substantive features) and the way in which the advertisement makes use of headings, different font sizes, the placement of graphics and so on (form features)..

Types of Content Analysis. Content analysis can be both quantitative (focused on counting and measuring) and qualitative (focused on interpreting and understanding). In both types, you categorize or “code” words, themes, and concepts within the texts and then analyze the results. Quantitative content analysis example To research the importance of employment issues in political campaigns, you could analyze campaign speeches for the frequency of terms such as unemployment , jobs , and work and use statistical analysis to find differences over time or between candidates ..

Qualitative content analysis example To gain a more qualitative understanding of employment issues in political campaigns, you could locate the word unemployment in speeches, identify what other words or phrases appear next to it (such as economy, inequality or laziness ), and analyze the meanings of these relationships to better understand the intentions and targets of different campaigns.

Applications of content analysis. Content analysis provides a structured way of analysing data that are typically open-ended and relatively unstructured. Two important aims of such analysis for business and management research are: Description Here the focus is on describing features of the message content. Jain et al. (2010), for example, study how the ways in which celebrities were presented in Indian television commercials varied according to the category of products they were promoting. Descriptive content analysis can be cross-sectional or longitudinal. An example of the latter is Paek et al.’s (2012) investigation of the promotion techniques used in cigarette advertising over a fifty-year period..

Prediction Here the main aim is to predict the outcome or effect of the messages being analyzed. Through the measurement of relevant features of the message, the researcher seeks to predict audience or receiver reaction (Neuendorf 2002). A study by Naccarato and Neuendorf (1998), for example, investigates how different features of print media advertising affected recall, readership and evaluation in a business-to business context. In that particular study, content analysis of the advertisements is combined with survey data to allow the researchers to assess the effect of particular features of the advertising. Content analysis has been applied to a wide range of social science topics including gender and race, violence, media reporting and political communication..

Insch et al. (1997) suggest its use is less common in organizational research due to lack of familiarity with the method. Nevertheless it has obvious applications in the analysis of business communication, particularly marketing. The rise of the analysis techniques to analyze online communication. Examples include Jose and Lee’s (2007) study of global corporations’ environmental reporting based on examination of their websites and Gebauer et al.’s (2008) analysis of online user reviews to identify requirements for mobile technology ..

Quantitative Content Analysis & Steps. Quantitative content analysis, “the systematic, objective, quantitative analysis of message characteristics” (Neuendorf, 2002, p. 1) Key Steps In Quantitative Content Analysis 1. Select the content you will analyze Based on your research question, choose the texts that you will analyze. You need to decide: The medium (e.g. newspapers, speeches or websites) and genre (e.g. opinion pieces, political campaign speeches, or marketing copy ) The criteria for inclusion (e.g. newspaper articles that mention a particular event, speeches by a certain politician, or websites selling a specific type of product). The parameters in terms of date range, location, etc..

If there are only a small amount of texts that meet your criteria, you might analyze all of them. If there is a large volume of texts, you can select a sample. For Example we select a topic to research media representations of younger and older politicians, you decide to analyze news articles and opinion pieces in print newspapers between 2017–2019. Because this is a very large volume of content, you choose three major national newspapers and sample only Monday and Friday editions . 2. Define the units and categories of analysis Next, you need to determine the level at which you will analyze your chosen texts. This means defining in the next slide:.

The unit(s) of meaning that will be coded. For example, are you going to record the frequency of individual words and phrases, the characteristics of people who produced or appear in the texts, the presence and positioning of images, or the treatment of themes and concepts? The set of categories that you will use for coding. Categories can be objective characteristics (e.g. aged 30-40 , lawyer , parent ) or more conceptual (e.g. trustworthy , corrupt , conservative , family oriented ). Your units of analysis are the politicians who appear in each article and the words and phrases that are used to describe them. Based on your research question, you have to categorize based on age and the concept of trustworthiness. To get more detailed data, you also code for other categories such as their political party and the marital status of each politician mentioned ..

3. Develop a set of rules for coding Coding involves organizing the units of meaning into the previously defined categories. Especially with more conceptual categories, it’s important to clearly define the rules for what will and won’t be included to ensure that all texts are coded consistently. Coding rules are especially important if multiple researchers are involved, but even if you’re coding all of the text by yourself, recording the rules makes your method more transparent and reliable. In considering the category “younger politician,” you decide which titles will be coded with this category ( senator, governor, counselor, mayor ). With “trustworthy”, you decide which specific words or phrases related to trustworthiness (e.g. honest and reliable ) will be coded in this category..

4. Code the text according to the rules You go through each text and record all relevant data in the appropriate categories. This can be done manually or aided with computer programs, such as QSR NVivo, Atlas.ti and Diction, which can help speed up the process of counting and categorizing words and phrases. Following your coding rules, you examine each newspaper article in your sample. You record the characteristics of each politician mentioned, along with all words and phrases related to trustworthiness that are used to describe them..

5. Analyze the results and draw conclusions Once coding is complete, the collected data is examined to find patterns and draw conclusions in response to your research question. You might use statistical analysis to find correlations or trends, discuss your interpretations of what the results mean, and make inferences about the creators, context and audience of the texts. Let’s say the results reveal that words and phrases related to trustworthiness appeared in the same sentence as an older politician more frequently than they did in the same sentence as a younger politician. From these results, you conclude that national newspapers present older politicians as more trustworthy than younger politicians, and infer that this might have an effect on readers’ perceptions of younger people in politics ..