Content Analysis Method in Global Affairs


Studies on global affairs focus on a wide area of political relations between countries, cultures, and administrations (Coppieters, 2015). The study of these international relations requires a methodical technique to find essential methods and forces of change. Analysis in international relations employs various methods, including the use of rational analysis and statistical methods. Content analysis is a research method used to identify patterns documented data (Lamont, 2015).

The information involved could be obtained from speeches, one-on-one conversations, films and photos, newspapers, and even Internet content. This method consists of employing both qualitative and quantitative or both means of research structures. This paper will be discussing content analysis as a method of research in international relations, the processes involved, the ideal data required, and the overall understanding of the method. The study of IR employs various research methods borrowed from other disciplines, from laws of economics, which lay the basis on which research is conducted (Lamont, 2015).

Quantitative Content Analysis

Numerical tactics require a more significant sample of instances representing and allowing inferences about an even larger population of cases. Such research depends on random selections to get a sample to represent. When used in the case of study methods, these requirements are not necessary though they are helpful in statistical methods. The study of international relations applies a diverse choice of methods; here, content analysis has been the method of choice in researching IR (Lamont, 2015). Research methods are techniques for collecting data; this is important as it allows the researcher to dig deeper into specific situations, places, and personas.

The first stages of content analysis require that the data be fragmented into pieces for sampling, collection, and examination, and reporting (Selzer King & McCarthy, 2018). This is particularly important to IR students in helping them decide on what type of data they will be working on. A researcher should determine the contextual questions that could come up in using the chosen method of interest.

This can be achieved through using the thesis and dissertations and previous works of other individuals in the context of global affairs and the methods of obtaining knowledge relating to epistemology and ontology (Lamont, 2015). The content in question is broken down into problems while focusing on each category on its own accord; information analysis should therefore be thorough and precise. Thus, the content analysis can be used to obtain the reasons, communications, and the effects of the messages of the content. It can also be used in quantifying the happenings of a given message in a historical setting.

Coding consistency should be enhanced, particularly when engaging more than one person in the coding process. This can be solved by developing a coding manual that indicates the names of the coders and guidelines on how the codes are allocated. One can also create a manual that allows them to take notes as the actual coding takes place. When employing the comparative method, the coding guidebook evolves the data analysis process and will be increased with informational communications. Triangulation is used to improve the credibility of qualitative data analysis in research related to international relations. Data is collected, examined, and substantiated on the question characteristic from several sources (Lamont, 2015).

Qualitative Content Analysis

During content analysis, several procedures are involved in ascertaining the given information (Lamont, 2015). The first step begins with generating the hypothesis moving from an advanced research convention in a deductive approach. The assumption flows systematically, starting from the known to the unknown, which it seeks to explain. The second phase involves identifying the appropriate data to be used in the analysis, and the statistics could be in text form, photographic material, or any communicative content. Hypothesis guides in defining the type of data required in the study question. The third step is to determine the sampling method and the sampling unit used in the content analysis.

In testing, the aim is to draw generalized assumptions about a given population by studying the sample size of the entire population. Researchers have used various methods to study global affairs, with most of them choosing to use qualitative methods. The scholars have been able to tell whether their objectives expressive, projecting, normative or explanatory. Researchers’ objectives have led to a discussion on whether the qualitative method should be used or not. The debate is yet to be solved soon, but meanwhile, they have urged people to use a variety of ways as they decide.

The fourth stage involves drawing an applicable sample that acts as a scheme to understand the rest of the content. The system creates categories that are effective and applicable to the type of data needed. Valid structures mean that the measuring technique symbolizes the required concepts. The fifth step in the content analysis procedure involves establishing a data collection unit and an analysis unit (Susanti, 2018).

The gathering of information is a crucial process as it will be the basis of conducting the research, and it involves several stages as well. First, the researcher summarizes the findings obtained when coding, constructing, and paraphrasing in a more understandable format. Then the expert receives and highlights the patterns and connections between their results which acts as a guide to them answering their research questions. Lastly, the examiner identifies and relays the relationship between their findings and other studies they encountered; this enables them to choose a perspective for the study (Moses & Knutsen, 2007.).

In discussing qualitative and quantitative data analysis, several similarities are noted in the two variants (Maurya, Gill & Goyal, 2017). First, both require a trial text that needs to select appropriate material, text unitization, which involves distinguishing words from examples, contextualizing the text, and having specific study problems in the back of the researcher’s mind. However, there are notable differences, which are seen in how the research questions are formulated, the selected sampling criterion, coding, and method of analysis involved. Unlike quantitative content analysis, which originates from a positivistic approach, qualitative analysis of content flows from a humanistic methodology and is inductive. The qualitative content analysis could return testable assumptions, but it is not its immediate intention (Moses & Knutsen, 2007.)

In sampling, the two methods require the researcher to choose the relevant text for the intended study procedures. However, qualitative content analysis concentrate on the text’s distinctiveness and are aware of the several meanings that could come from the keen scrutiny of the text.

Close analysis of the text always leads to limited size of sample. Also, since qualitative research does not aim at generalizing content but transferring, then sampling needs not to make sure that the contents being scrutinized have a similar likelihood of being added into the sample. Selection should instead be hypothetical and intentional since findings are transferred from one context to another (Lamont, 2015). Analyzing fresh content should be reiterated until no new results are gotten, and in this case, it is assumed that all appropriate patterns have been found, and further work would confirm that.

Developing a coding system can either be done inductively or deductively. When faced with a study question lacking assumptions, categories are to be inductively generated from the given data. This approach is appropriate when the study question requires one to develop a theory and not those that are out to describe an inevitable occurrence or prove an existing concept. Using the proportional procedure is to understand the hypothetical properties of the group wholly and integrate the groups and their properties through the expansion of explanatory communications. The quantitative content analysis uses groups that are meant to be jointly particular because similar variables could go against the assumptions of some statistical processes (Zheng, Zhang & Tong, 2016).

Computer Software in Content Analysis

One could also consider engaging computer software depending on the amount of content there is to be analyzed due to the large databases available in international relations research (Moses & Knutsen, 2007). Computer programs could assist in research work by quickly marking up data, grouping information into analyzable portions, note-making, putting together any related data, and making it available for international editing.

The software could also extract and manipulate data, corresponding the text against particular vocabularies for coding reasons. Furthermore, computers could be used resourcefully to collect, electronically maintain the coded data and record-keeping of all the steps involved in the content analysis (Slayter, 2016). Lastly, the computer software can perform quantitative analyses, calculate percentages, and obtain frequency counts. This can be done either in the software itself or transferring the data to a statistical package, thus minimizing errors when working on multiple sets of data. The statistical software package could mainly permit inferential figures.

The statistical programs organize themselves on a range from efficiently assisting a human’s coding of the electronic data to straight participation in examining the document at hand (Firth, 2019). The software is also involved in related terms to those of an electronic dictionary, which is used to create a coding scheme and code the data. The programs allow for storing all forms of data from textual documents to electronic audios and images.

Qualitative content analysis mostly depends on explanatory aids (Moses & Knutsen, 2007). In contrast, dictionary-based data analysis mostly depends on various functions such as name and group computations, incidence studies, visualization, and occasionally concordance groups. Some software also records the researchers’ coding history to allow the researchers to keep track of their work progress.


Qualitative content analysis is a valued substitute to the highly conventional quantitative content analysis technique, as the researcher keeps working on an informative hypothesis. The intention is to ascertain significant themes or classifications in the body content and deliver an appropriate explanation of the categories’ societal authenticity as they are outlined in a specific situation. Through careful data research, coding, and understanding qualitative content analysis outcomes, can sustain the progression of new concepts and prototypes and authenticate general concepts, and provided that thick explanations of specific settings or occurrences.

This work classifies content analysis as a methodically engaging approach to scrutinizing work produced in conducting research. It concisely discusses the processes involved, notes the differences between qualitative and quantitative analysis, and illustrates the importance of both research approaches.


Coppieters, B. (2015). Recognition in international relations: rethinking a political concept in a global context. Global Affairs, 1(4-5), 473-475. Web.

Firth, C. (2019). Protecting investors from themselves: evidence from regulatory intervention. SSRN Electronic Journal. Web.

Lamont, C. (2015). Research methods in international relations (pp. 13-28).

Maurya, V., Gill, A., & Goyal, A. (2017). A new two-stage multiple comparison procedure for comparing several exponential populations with control under heteroscedasticity. Computational statistics & data analysis, 108, 1-11. Web.

Moses, J., & Knutsen, T. (2007). Ways of Knowing: Competing methodologies in social and political research (pp.24-112). Publisher Palgrave Macmillan Limited.

Selzer King, A., & McCarthy, M. (2018). Artifactual Dimensions of Visual Rhetoric: What a Content Analysis of 114 Peer-Reviewed Articles Reveals about Data Collection Reporting. Technical Communication Quarterly. Web.

Slayter, E. (2016). Teaching note — “By any means necessary!” Infusing socioeconomic justice content into quantitative research course work. Journal of social work education, 53(2), 339-346. Web.

Zheng, J., Zhang, G., & Tong, C. (2016). Estimating the self-similar exponent of broad-sense self-similar processes. Physica A: Statistical mechanics and its applications, 444, 654-659. Web.

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