Decomposing the Fundamentals of Creepy Stories
Sakshi Goel, Haripriya Dharmala, Yuchen Zhang, Keith Burghardt

TL;DR
This paper analyzes thousands of scary stories from Reddit to understand what makes stories frightening, identifying stable linguistic features, evolving themes, and developing a neural network to detect fear expressions within stories.
Contribution
It introduces a comprehensive analysis of scary story themes and writing styles over time and presents a high-accuracy neural network for fear detection in narrative texts.
Findings
Themes shifted from haunted houses to school, body horror, and diseases.
Words like clown and devil are more common in scary stories.
Fear expressions spike at specific story points.
Abstract
Fear is a universal concept; people crave it in urban legends, scary movies, and modern stories. Open questions remain, however, about why these stories are scary and more generally what scares people. In this study, we explore these questions by analyzing tens of thousands of scary stories on forums (known as subreddits) in a social media website, Reddit. We first explore how writing styles have evolved to keep these stories fresh before we analyze the stable core techniques writers use to make stories scary. We find that writers have changed the themes of their stories over years from haunted houses to school-related themes, body horror, and diseases. Yet some features remain stable; words associated with pseudo-human nouns, such as clown or devil are more common in scary stories than baselines. In addition, we collect a range of datasets that annotate sentences containing fear. We…
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Taxonomy
TopicsMisinformation and Its Impacts · Mental Health via Writing · Sentiment Analysis and Opinion Mining
