What is AI Story Analytics?

Storytelling is human nature

StoryFit is single-mindedly focused on applying the latest AI technology to the entertainment industry. We’re passionate about the intersection of technology and media and dedicated to improving the process of storytelling.

Our artificial intelligence service is specifically built to solve the most common challenges publishing and entertainment companies face in delivering the right content at the right time and to the right audience. We bring deep content and audience insight to editorial development, marketing, and sales while reducing risk, costs and delays

As so much of the history of artificial intelligence makes clear, humans are driven by a desire not just to communicate, but to understand the nuances and meaning of that communication beyond just the words on the page. To understand why the words make us stir, incite violence, or begin profound romance.

Beginning with asking kindergartners to draw themselves with their parents at home, we have to be taught narrative form as children to help us make order of the world around us. To derive meaning from apparently meaningless occurrences and assign value to relationships. It all comes back to story: a universal logic system. Inciting action, climax, falling action, resolution. Cause and effect. Consequence and reward. Villains and threats, heroes and allies. All of these significant and community-forming concepts are conveyed through story form. So understanding stories is one of the most resonant way to understand human desire, development, and potential.

We see this fact reflected in our books and movies. We don’t sit down to enjoy textbooks or manuals, and we don’t recline on a sunday afternoon in front of the television to watch training videos and sexual harassment protocols. Arguably, all would be more materially productive, but they don’t satisfy that basic human need to understand the world through story. To engage in empathy and learn. Stories are the basis of every viable form of media — movies, books, television, video games, RPGS, etc.

By focusing on that core story through machine learning, StoryFit is able to deliver better analytics that can tell users meaningful information about their customers and content, insights that will prove useful and meaningful to other projects and give them the tools to connect meaningfully and quickly with their audience.

Afterall, as Google Engineer Inderjeeet Mani said, “computer science isn’t as far removed from the study of literature as you might think.”

Using data to mine stories

By creating rules for a computer to recognize story elements and emotions help us mimic human experience for study. Those rules start with natural language processing and sentiment analysis which are able to infer the emotions different linguistic styles, circumstances, diction, and perceived emotional arc evoked in readers.  

At a glance, sentiment analysis is fairly straightforward: text is analyzed and, using natural language processing, each part of the text is categorized positive–happy statements–or negative–sad/angry statements. Within each language, words can be determined positive (elated, kiss, jump), negative (smash, kill, cry), or neutral (the, a, road). Take these altogether and graph the results, and you can see the emotional arc of a text mapped out in a physical form, called a sentiment map.

This is just the beginning, from there we can group the language, with the surrounding action, and the thousands of other features we measure to infer how a human might connect to a particular emotional arc.  Of course, AI is as good as the data it’s fed and the direction it’s given. In this case, AI is created through a process of machine learning, whereby it basically uncovers and then replicates automated decision-making based on the parameters it’s delivered. Then we can then check our work with real humans!

Once the algorithm is well-trained and directed, then AI is reliable. For one thing, it’s consistent. It doesn’t get tired, need to take a break, or get distracted by personal reading preferences.

Humans are amazingly creative, observant, and resourceful. But at a certain point, our brains just can’t process any more data any more quickly.

Meanwhile, a computer using AI continues doing the task at hand, not changing it’s analysis due to fatigue, overwork, boredom, or a headache.

Using Data to Amplify Human Creativity

The goal of machine learning or artificial intelligence is not to replicate human creativity, but instead amplify it.  At StoryFit, our AI is not built to proscribe quality or replace the editor. It empowers them with more data than they could ingest in a lifetime, distilled into actionable insights.

The benefit of a computer doing the analysis is that it can discover the latent aspects of a novel. So, while authors may have their own identifiable style, there are underlying components of a novel that a computer can see better than humans.

Books hold undeniable cultural weight– and they are also data.  Unlike consumer data that, even formless, has proven itself so valuable, text has inherent rules and formations. And each deviation from one rule has its own set of rules, deviations, and acceptable actions that AI can learn, compare, and predict, just like humans can.

When book clubs discuss a possible connection of a white lily to the heroine’s inevitable death, they are discussing the pattern identified in a semi-closed system. They are performing one tiny fraction of the computational potential of an algorithm trained on literature.  

StoryFit integrates data, elemental story analysis, and market research to improve audience targeting, determine market fit, and mitigate investment risk. Everything you need to quickly and painlessly make informed decisions, edge the competition, and drive consumer engagement.

Implementing Story Analytics

AI holds a lot of future payoff for publishers who implement it early and often. Since it can learn, the real issue is what question do you want to tackle first? At StoryFit, we see direct and immediate impacts to discoverability, audience targeting and engagement, recommendation engines, efficiency, and acquisition risk assessment.

Specifically, AI in a publishing and production environment can:

• Metadata & Discoverability
• Data integration
• Reader Analytics
• Improve Audience Targeting and
• Increase Audience Engagement
• Predict mass audience (bestseller) appeal

Publishers can take advantage of this in three applications:

1. StoryFit Intelligent Metadata

StoryFit uses AI to craft metadata that increases discoverability, engagement, and sales. Supplying metadata is proven to enhance discoverability–accurate metadata further increases both discoverability  and sales for new and existing content.

AI scans the text of a story and extracts the words, phrases and terms that describe the story’s content, impact, and sentiment and pulls the key elements important to readers–character types, conflict types, setting, era, , and more–for your keywords. These words are compared to and filtered through dictionaries, topic models, Google trends, and best industry and Amazon practices to determine their effectiveness to drive consumer discovery.

The software further analyzes, tests and updates the keywords for improved performance. Intelligent Metadata generated by StoryFit™AI provides our customers with the right metadata, optimized for accuracy, performance, and that conforms to major distributor/resellers’ requirements. Intelligent Metadata allows publishers to give each title more room to succeed and breath life into classics or titles that just never found their audience with optimized keywords that respond to sales performance and market behavior.

2. StoryFit Content Analytics

Our content insights and analytics enable publishers and studios to learn their stories’ secrets, support decisions, pitches and process with data built from industry bestsellers and veteran wisdom. StoryFit™ reads your text in seconds and measures it against key points that have proven correlations to commercially successful outcomes.The metrics result from analysis of thousands of high-performing titles and allow publishers and producers to find new titles with the best chance of success and better position existing investments, identify better comps, and kickstart marketing.

Included in the content analytics are market readiness ratings, style insight, story arc, faceted comps,  accessibility index, and predictive audience profiles.

3. StoryFit Custom AI Story Analytics

StoryFit AI can learn and adapt to its environment; by listening to your business problems, and analyzing your specific data—be it customer profiles, sales history, web behavior, and more. —  StoryFit can tailor a solution just for you.

By applying our algorithms to your proprietary data and publicly available information you can create a tactical maneuver that amplifies your strengths and allows you to move faster than your competitors. Just some ways publishers can design their own AI with StoryFit are to:

• Superpower your own recommendations engine.
• Rapidly identify important performance indicators and categorize content to suit your marketing goals.
• Use own top performers as a rubric to find new material and uncover potential powerhouse titles in your backlist
• Surface new audiences for old content, and new content for your loyal audiences
• Identify manuscripts that match your unique editorial tastes and generate comps from your own library.