Methods of qualitative data analysis are the key to successful qualitative research. Qualitative research is essential because it answers research questions and enables a deeper understanding of experiences, phenomena, and contexts. However, in many very complex studies, the quantitative research design is very difficult or impossible; In this situation, using a qualitative research method is an appropriate option. In the previous article on the smart strategy blog, we deep dive into the qualitative data analysis introduction. In this blog, we want to introduce and express the components of various qualitative data analysis methods.
introduction to methods of qualitative data analysis
Phenomenological analysis: the most brutal forms of qualitative data analysis
The phenomenological analysis is one of the most difficult qualitative data analysis methods because its philosophical dimension is much broader and deeper than its practical dimension. The purpose of the phenomenological analysis is to understand and extract the intrinsic meaning of the phenomenon or the essence of the phenomenon under study. Phenomenological approaches may be applied individually or in groups, and various methods may be used, including interviews, participant observations, hands-on research, focus sessions, and personal text analysis. Phenomenology encourages the researcher to be as close to the subject matter’s essence.
The steps of designing and performing the phenomenological qualitative data analysis method are as follows:
- First, the researcher begins the analysis with a complete description of their experience with the phenomenon under study
- The researcher finds phrases (in interviews) about how people experience the subject. They list these essential phrases. It then considers each of these expressions with the same value. Finally, he tries to list repetitive propositions.
- It then groups these phrases into meaningful units, lists them, and creates a description of the textual context of the experience (textual description).
- At this stage, the researcher expresses his description and uses imaginative variety and structural characterization; It means searching for all possible meanings.
- The researcher then provides a general description of the meanings and nature of the phenomenon experienced.
- This process is followed to report the researcher’s experience and then perform for each participant. Finally, a description and a combination of all the illustrations are written separately.
Qualitative content analysis
Content analysis is one of the main methods of viewing documents by which texts and documents can be regularly evaluated and analyzed. In a general classification, different methods of content analysis are divided into two broad categories: quantitative content analysis method and qualitative content analysis method.
In quantitative methods, large amounts of data are usually briefly analyzed. In this method, a set of documents or texts can be extracted, counted, and classified. In qualitative methods, small amounts of complex and detailed data are analyzed. The content analysis method initially focused on quantity and counted the frequency of the presence of an analytical unit, such as a word or a term in the text. This way of thinking gradually changed, and parts of it were corrected and revised. This method has become a synthetic content analysis in which both explicit and implicit meanings are identified and counted. Currently, qualitative content analysis is the same as thematic or theme analysis.
In addition to the qualitative content analysis method, the conversation analysis method is also used. This method analyzes conversation behavior; its rules and patterns are inferred and formulated. One of this analysis’s most important theoretical foundations is that it focuses on analyzing spoken texts in natural situations, not in the laboratory.
The basic premise of this analytical approach is that the people of each society have specific procedures for giving meaning to their daily lives. In this context, language is critical as a relation and mediator of the social world.
The steps of this method of qualitative data analysis are as follows:
- First, specify the text of the conversation: Select the text of the conversation or conversation. This text may vary from a telephone conversation to the text of dialogue in a novel.
- Determining the unit of study: The unit of analysis may be a word, a sentence, a paragraph, or a chain of conversation.
- Identify the logic of the conversation: The conversation chain, the conversation’s beginning and end, and other specific dimensions of the discussion should be considered.
- Final analysis and interpretation: The relationship between the dimensions and contents of the conversation text is analyzed and interpreted.
In this qualitative data analysis method, sign language is defined as a symbol in which each sign gives meaning to another character. The study of various systems of symptoms, such as mathematics, music, street signs, and the like, can be done by semiotic analysis. This method is based on analyzing language in the context being read. In semiotic analysis, the researcher seeks to identify hidden layers, unknown dimensions, specific meanings, and the semantic system behind the signs.
It distinguishes three types of semiotic methods in qualitative research: sign clustering, semiotic chain, and semiotic squares.
Semiotic clustering: In this method, a table with three columns called competing meanings, revealed meanings, and institutional considerations are drawn.
Semiotic Chains: A semiotic map is presented based on how the underlying structure is constructed in typical signs. This can be done by drawing a series of semantic diagrams.
Semiotic squares: This method involves a system of rules or grammar through which meaning is produced.
The thick description method is more of an outline, methodological recommendations, or method of receiving and writing than a conventional research method.
The thick description includes a description of the environment, participants, events, themes, etc., in detail that conveys the story to the reader. These details enable readers to make a natural connection between their narrative experiences and their personal experiences. In other words, in a thick description, the researcher describes the multiple layers and multiple dimensions of the text, phenomenon, event, or reality with precision, delicacy, and patience. For example, if a researcher thickly describes a particular deviant behavior, they will also naturally address the causes and consequences of that behavior.
The general steps for applying a thick description are as follows:
- First, the text, phenomenon, event, context, or any cultural theme of interest is selected.
- The researcher immerses herself in her subject and explores it with an intimate experience.
- Each of the elements of the subject is explained in such a way as to reach descriptive saturation.
- The thick description does not mean overwriting but rather revealing the semantic system in the text or phenomenon.
- It focuses on meanings, symbols, signs, links, and connections in “their contexts.”
- The facts in the phenomenon or any social text under study are flipped through, and their layers are opened like the layers of an onion to reach its true core.
- Writing a thick description report is primarily creative, but the general steps of qualitative reporting can be used.
Situational analysis: new methods of qualitative data analysis
Situational analysis is one of the very new methods of qualitative analysis for analyzing social phenomena, whether textual or non-textual. Situation analysis seeks to apply ground theory to fluid, floating, ambiguous, and postmodernist multidimensional situations. According to situational analysis, the position of action is composed of many different and complex dimensions and elements that classical ground theory cannot understand and represent it. The situational analysis method emphasizes other forms of analysis, especially narrative, discourse, and qualitative content analysis. Hence, situation analysis is a method of multiple analysis.
To achieve the goal of situational analysis, situation maps, world / social arena maps, and status maps are used at the heart of the situation analysis method.
- Situational maps: These maps are used as strategies for articulating the elements in a situation and examining the relationships between them.
- Maps of worlds / social arenas: used as a cartography of commitments, commitments, public relations, and places of action.
- Situation maps: Used as simplification strategies to draw articulated and articulated situations in discourses.
This qualitative data analysis method pays attention to words, sentences, and linguistic characteristics. In other words, focus on the way language is used. How is the language used? What is it used for? What are its application contexts? This type of analysis is called discourse analysis.
Discourse analysis is a significant development in qualitative research and begins with the assumption that discourse is essential at all levels, from individual reports to social reports.
In general, the main activities during discourse analysis are as follows:
- Targeting: Expressing the purpose of conducting discourse analysis.
- Marking: Finding semiotic and thematic clues in the text.
- Word formation: examining the words in the text in terms of real/unreal elements, probable / unprobable, possible/impossible, present/absent, and the like.
- Activation: Revealing activities and actions within the text or phenomenon.
- Cultural and social sensationalization: analysis of different situations within the text.
- Identification and relationship building: Attention to attitudes, identities, interactions, and communication contexts within the text.
- Politicization: Considering dimensions such as ideology, power, inequality, knowledge, class, base, domination, etc.
- Connection: Examining the past, present, future, or time chain of text or discourse elements.
Observational data analysis
Observational data, like textual data, are analyzed in different ways. Although observational data are used in various qualitative data analysis methods, they are mainly studied in thematic analytical procedures and critical ethnography.
Observational data, especially data collected during fieldwork and ethnography, can be divided into two categories: textual observational data and visual observational data.
- Textual observation data: This data includes the researcher’s notes and records of the dimensions of the phenomenon or field under study. This type of data can be generated through note-taking. Field notes include scattered notes, direct observation notes, and researcher inferential notes.
- Visual data: This type of data includes images and videos, sketches, and other visual data that the researcher collects in the research field. Image data can be categorized and analyzed in in-image encoding and inter-image encoding.
- In-image coding is the extraction of meanings and concepts within an image or a film by encoding the internal space of the image or image.
- Inter-image coding means that each image is encoded as containing a primary coded subject that, together with a chain of other photos, helps to understand the phenomenon or issue under study.
Since data analytics is one of the primary services of Smart Strategy, we try to provide complete information about data analysis in the Smart Strategy Blog. In this article, we offer a comprehensive introduction to qualitative data analysis methods necessary for successful qualitative research. If there is any question, contact us.
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