In a modern society saturated with content, it is often the case that understanding how a story is being told is just as important as what is actually being said. In this regard, narrative data analysis becomes a vital approach for exploring how meaning is constructed, communicated and then reinforced through targeted storytelling. Through analyzing the delivery and structure of things like social media posts, speeches and news articles, it is possible to gain precious insights into strategy, public perception and more.
With the help of narrative analysis software, this approach is widely used across sectors such as political science, journalism, national security and media research, all fields in which perception is critical.
Narratives are much more than just a collection of the facts, they are carefully put together expressions of meaning making. A narrative combines elements such as characters, setting, conflict and resolution in order to form a coherent story that resonates emotionally.
Examples of narrative data include:
• Campaign slogans and/or political speeches.
• Opinion pieces and/or editorials.
• Viral posts or social media threads.
• Video commentaries and podcasts.
• Crisis communication and/press briefings.
• Visual media in the form of memes, infographics and more.
What sets narrative data apart is the fact that it is designed to tell a story, presenting a specific point of view intended to evoke emotion or frame a certain issue through a certain lens. When considered under this light, it isn’t just the content that matters, but also the tone, narrative structure and any repetition of key ideas.
So, what is narrative analysis? There are a number of different models that can be used when approaching narrative data analysis, each offering unique insights. Some of the most commonly used techniques in the research process include:
A method that examines how a story is built by identifying the key elements that are making the narrative more persuasive or compelling:
• Beginning - the setup.
• Conflict - the challenge or tension raised.
• Resolution - the proposed solution or outcome.
Mapping the flow in this way can help an analyst to uncover how a story is designed to guide an audience to a particular conclusion.
Helping to understand messaging tactics used, and how leaders work towards shaping public opinion.A method that works to examine how language can shape authority, power and ideology. Key focus is paid on choice words, metaphors and tone, which is used to uncover underlying intentions beneath the surface of a message.
Frame analysis is a method that centers the question of how an issue is being presented. It considers which facts are being emphasized and which are being ignored, alongside the language being used to construct a leading perspective.
Combined, all of the approaches mentioned above allow for narrative data analysis to separate the layers of a message and identify its mechanisms.
Narrative text analysis plays a crucial role in configuring how people understand the world, both in the context of global events and everyday life.
Politicians will often reuse a set of familiar storytelling patterns, such as the underdog narrative, a call to restore ‘lost greatness’ or professing to be a people’s savior. These kinds of narratives have a high resonance rate across diverse audiences. A narrative analysis example in this field will involve comparing speeches across an election to pick up on repeated language and themes.
Various news organizations can report on an identical event using distinctly different framing. While one outlet might describe a protest as a justice fight, another can label it as violent civil unrest. In depth narrative text analysis can provide insight into how different framing effects that way an audience interprets a single story.
In the middle of emergency situations like military conflicts or national/global health crises, authorities will often seek to shape a narrative to foster calm, resilience or compliance. Repeating messages of safety and unity will usually follow a defined narrative structure that is designed to guide emotional response and behavior.As you can see, these narrative research examples highlight how storytelling isn’t just ‘artistic’, it is also incredibly strategic.
The task of scanning through thousands of messages manually for patterns can be incredibly time consuming, and potentially prone to error. To avoid mistakes and missing key insights, Osavul’s powerful suite of narrative data analysis tools can be of great assistance.
Osavul enables users to do the following:
• Detect and map any recurring narrative patterns that are identified.
• Analyze large scale messaging across a number of languages and platforms.
• Track the development of a story over time and regions.
• Identify any communication efforts that might be coordinated.
The combination of machine learning and insights gained from narrative research methods means that Osavul can analyze data that might otherwise be too overwhelming.
From brands to governments and more, there are a number of reasons why organizations choose to prioritize narrative content analysis. Storytelling can influence everything from emotional response to belief to behavior, and being able to understand stories enables better communication and audience engagement, as well as early detection of potential harmful narratives.
Some of the biggest narrative data analysis benefits include:
• Finding influence campaigns in real-time.
• Rapid response to any misleading or damaging content.
• Creation of proactive communication strategies.
• Better situational awareness in a fast moving information landscape.
In introducing narrative inquiry data analysis to their system, organizations put themselves in a much better position for public response and strategic planning.
In practical terms, applying narrative text analysis will commonly involve:
• Mapping character roles to establish if there is a villain or hero.
• Clustering together messages and phrases that repeat over time.
• Providing visualization of how a story can spread and evolve.
• Comparing both ideological and regional variations in a narrative delivery.
When gathered from narrative data analysis, these kinds of insights can help organizations in guiding things like coalition building, product development and overall public engagement.
With today’s world being so interconnected and saturated in media, the process of decoding stories is absolutely essential. Narrative data analysis provides a much deeper dive into things like emotion, structure and intent behind a message.
Thanks to tools like Osavul, a task that could be incredibly time consuming if done manually becomes much more accessible and insightful, especially when combined with strong narrative research methods.
When organizations choose to embrace narrative inquiry data analysis, they gain much needed clarity that leads to adapting and connecting in much more intelligent ways.
