Understanding when and why consumers engage with stories is crucial for content creators and platforms. While existing theories suggest that audience beliefs of what is going to happen should play an important role in engagement decisions, empirical work has mostly focused on developing techniques to directly extract features from actual content, rather than capturing forward-looking beliefs, due to the lack of a principled way to model such beliefs in unstructured narrative data. To complement existing feature extraction techniques, this paper introduces a novel framework that leverages large language models to model audience forward-looking beliefs about how stories might unfold. Our method generates multiple potential continuations for each story and extracts features related to expectations, uncertainty, and surprise using established content analysis techniques. Applying our method to over 30,000 book chapters from Wattpad, we demonstrate that our framework complements existing feature engineering techniques by amplifying their marginal explanatory power on average by 31%. The results reveal that different types of engagement-continuing to read, commenting, and voting-are driven by distinct combinations of current and anticipated content features. Our framework provides a novel way to study and explore how audience forward-looking beliefs shape their engagement with narrative media, with implications for marketing strategy in content-focused industries.

Intellectual property is the lifeblood of entertainment, and Hollywood badly needs a transfusion. Stuck recycling the same ideas and producing the same franchises, Hollywood is now looking to podcasts, news articles, and even songs and paintings to dredge up stories that could be hits with global audiences. Finding the right stories--and developing them into things that actually exist on screen--can be an arduous, money-draining process. One company thinks it has found an efficient new way to sift through millions of user-generated stories to find the next Hollywood hits: artificial intelligence. And, on occasion, it actually brings fans of those stories into the arcane process of developing them for the screen.

The best games of 2019 are a throwback. That appears to be Apple's take on things, anyway, as evidenced by at least some of the company's picks for the best apps and games for its hardware platforms. Consider Apple's choice for the "game trend of the year." App Store editors lumped a variety of apps into a category dubbed "Blockbusters Reborn," essentially fresh takes on familiar, and in some cases, decades' old franchises. You'll find "Mario Kart Tour" from Nintendo in this select grouping, along with "Minecraft Earth" (Mojang), "Pokémon Masters" (DeNA Co), "Assassin's Creed Rebellion" (Ubisoft), "Gears POP!" (Microsoft), "The Elder Scrolls: Blades" (Bethesda) and "Call of Duty: Mobile" (Activision Publishing).

Wattpad enables writers to create their own stories and share them with over 70 million users. Co-Founder and CEO Allen Lau explains to Anthony Lacavera how their Story DNA machine learning technology discovers and recommends the best content.

It is often written that technology isolates us. Too many opinion pieces blame our screens for the loss of human interaction. Virtual reality is painted as a false experience, ultimately empty of emotional connection. The truth is our gadgets are m...

"Bad Robot" is a Short Story about the accidental release of a super-efficient killing machine which threatens to set the entire world on fire. This story is part of a larger anthology series titled "The Apocolypse is Always Tomorrow" that I am curr...

If you are one of the 40 million people who enjoy reading or writing the mostly romantic werewolf, superhero or historical fiction stories found on Canadian startup Wattpad, you may also be contributing to the development of the next generation of artificial intelligence. In a new paper called Augur: Mining Human Behaviors from Fiction to Power Interactive Systems, a group of Stanford University computer science researchers revealed that they used the Wattpad "corpus" – a collection of almost two billion words (or 600,000 chapters) written by regular people – to help a computer understand the world around it. The team intends to make the program they built, Augur, into an open-source tool that other researchers can build on. "The basic idea is that it's very difficult to program computers to understand the broad range of things that people do," says fourth-year PhD student Ethan Fast, co-author of the paper (published as part of the upcoming Computer Human Interaction conference) and a member of Stanford's Human-Computer Interaction Group. "Fiction has a lot of useful things to say about the world, and if you have enough of it, you can model it in much more depth than you could hope to manually."