Speaker 1: In this video, we're going to unpack the sometimes slippery topic of narrative analysis. We'll explain what it is, consider its strengths and weaknesses, and look at when and when not to use this analysis method. By the end of the video, you'll have a clear overview of narrative analysis so that you can make well-informed decisions for your research project. By the way, if you're currently working on a dissertation, thesis, or research project, be sure to grab our free dissertation templates to help fast-track your write-up. These tried and tested templates provide a detailed roadmap to guide you through each chapter section by section. If that sounds helpful, you can find the link in the description below. So what exactly is a narrative analysis? Well, simply put, narrative analysis is a qualitative analysis method focused on interpreting individual human experiences and motivations by looking closely at the stories, the narratives, people tell in a particular context. Narrative analysis can draw on various sources, including interviews, monologues, written stories, or even recordings. In other words, it can be used on both primary and secondary data to provide evidence from the experiences described. Now that's all quite conceptual, so let's look at an example of how narrative analysis could be used in practice. Let's say you're interested in researching the beliefs of a particular author on popular culture. In that case, you might identify the characters, the plotlines, symbols, and motifs used in the stories that they write. You could then use narrative analysis to analyze these factors in combination and against the backdrop of the relevant context. This would allow you to interpret the underlying meanings and implications in their writing, and to pick apart what these reveal about the beliefs of the author. In other words, you'd look to understand the views and beliefs of the author by analyzing the narratives that run through their work. Generally speaking, there are two approaches that one can take to narrative analysis. Specifically, an inductive approach or a deductive approach. The approach you take, inductive or deductive, will have a significant impact on how you interpret your data and the conclusions you can draw from it. So it's important that you understand the difference between these two approaches. First up is the inductive approach to narrative analysis. This approach takes a bottom-up view, allowing the data to speak for itself without the influence of any preconceived notions. With the inductive approach, you begin by looking at the data and deriving patterns and themes as opposed to viewing the data through the lens of pre-existing hypotheses, theories, or frameworks. In other words, the analysis is led by the data. For example, with an inductive approach, you might notice patterns or themes in the way an author presents their characters or develops their plot. You'd then observe these patterns, develop an interpretation of what they might reveal within the context of the story, and draw conclusions in relation to your research aims. Contrasted to this is the deductive approach. With this approach, you begin by using existing theories or frameworks that a narrative can be tested against. Here, the analysis adopts particular theoretical assumptions and or provides hypotheses and then looks for evidence in a story that will either verify or disprove them. For example, your analysis might begin with a theory that wealthy authors only tell stories to garner the sympathy of their readers. Taking a deductive approach, you might then look at the narratives of wealthy authors for evidence that will substantiate or refute your theory. You would then draw conclusions about the accuracy of the theory and suggest explanations for why that might be the case. So to recap, a narrative analysis can be undertaken using either an inductive approach, where you're letting the data speak for itself and taking a more exploratory view, or you can take a deductive approach, where you're testing your data against an existing theory and assessing its accuracy. In other words, you're taking a more confirmatory view. Now that we've covered what narrative analysis is, it's important to discuss the strengths and weaknesses of this analysis method so that you can make the right choices in your research project. A primary strength of narrative analysis is the rich insight it can generate by uncovering the underlying meanings and interpretations of individual human experiences. The focus on an individual's narrative highlights the nuances and complexities of their personal experience, revealing details that might be missed or considered insignificant by other analysis methods. This makes it especially useful for those of you who are researching topics related to psychology, sociology, ideology, or cultural studies. Another strength of narrative analysis is the range of topics it can be used for, as well as the data formats it can be applied to. As an analysis method, it can be used on a wide range of data sources, including written texts, interviews, monologues, and recordings. This ability to apply narrative analysis to both primary and secondary data makes it a very flexible analysis method. All that said, just like all analysis methods, narrative analysis has its weaknesses, and it's important to understand these so that you can make informed decisions for your research project. The first drawback of narrative analysis is the problem of subjectivity and interpretation. In other words, a disadvantage of the focus on stories and their details is that they're open to being understood differently depending on who's reading them. This means that a strong understanding of the author's cultural context is crucial to developing your interpretation of the data. At the same time, it's important that you remember At the same time, it's important that you remain open-minded in how you interpret your data and avoid making any assumptions. It's a tricky balance, I know. A second weakness of narrative analysis is the issue of Since narrative analysis depends almost entirely on a subjective narrative and your interpretation, the findings and conclusions can't usually be generalized or empirically verified. Although some conclusions can be drawn about the cultural context, they're still based on what will almost always be anecdotal data and therefore wouldn't necessarily be suitable for the basis of a theory, for example. Last but not least, the focus on long-form data means that narrative analysis can be very time-consuming. Not only will you need to invest a significant amount of time to become well-versed with the data itself, but you'll also need to be well-informed regarding the author's cultural context. Ideally, you should also familiarize yourself with other interpretations of the narrative to ensure that you have a holistic view. So, if you're going to undertake narrative analysis, make sure that you allocate a generous amount of time to work through the data. If you're enjoying this video so far, please help us out by hitting that like button. You can also subscribe for loads of plain language, actionable advice. If you're new to research, check out our free dissertation writing course, which covers everything you need to get started on your research project. As always, links down in the description. Okay, so now that we've unpacked the basics of narrative analysis, as well as its strengths and weaknesses, let's have a look at when you should use it. So basically, when exactly is narrative analysis an appropriate method? As a qualitative method focused on analyzing and interpreting narratives, describing human experiences, narrative analysis is usually most appropriate for research topics that are focused on social, personal, cultural, or even ideological events or phenomena, and how they're understood at an individual level. For example, if you were interested in understanding the experiences and beliefs of individuals suffering social marginalization, you could use narrative analysis to look at the narratives and stories told by people in marginalized groups to identify patterns, symbols, or motifs that shed light on how they rationalize their experiences. In this example, narrative analysis presents a good natural fit, as it's focused on analyzing people's stories to understand their views and beliefs at an individual level. Conversely, if your research was geared towards understanding broader themes and patterns regarding an event or a phenomena, analysis methods such as content analysis or thematic analysis may be better suited. Well, depending on your research aim, of course. If you're interested in learning more about those methods, we've got videos covering them as well. Links are in the description below. All right, we've covered a lot of ground in this video, so let's do a quick recap. Narrative analysis is a qualitative method focused on interpreting human experience in the form of stories or narratives. We've discussed two approaches to narrative analysis, the inductive approach, where your interpretations and conclusions are drawn exclusively from observations within the data, and the deductive approach, where your selected narrative or stories are tested against pre-existing theories, frameworks, or hypotheses. Like all analysis methods, narrative analysis has a particular set of strengths and weaknesses. Based on those, narrative analysis is generally most appropriate for research that's focused on interpreting individual human experiences as expressed in detailed long-form accounts. If you got value from this video, please hit that like button to help more students find this content. For more videos, check out the Grad Coach channel, and make sure you subscribe for plain language, actionable tips and advice regarding all things research-related. Also, if you're looking for one-on-one support with your dissertation, your thesis, or your research project, be sure to check out our private coaching service, You can learn more about that, and book a free initial consultation at gradcoach.com.