Summary The Emotional Arcs of Stories A Study arxiv.org
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The study analyzed over 1,700 books to identify six core narrative arcs, revealing genre and cultural differences with potential applications in creative writing and analysis.
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Key Points
- The study identified 6 core emotional arcs that capture the majority of variance in the emotional trajectories of over 1,700 stories: rags-to-riches, tragedy, man-in-a-hole, Icarus, Cinderella, and Oedipus
- Certain emotional arcs, like Icarus, Oedipus, and sequential man-in-a-hole, were associated with more successful and popular stories as measured by downloads
- The emotional arcs tended to cluster by genre, with romance novels often following the Cinderella pattern and horror stories more likely to exhibit the man-in-a-hole arc
- The researchers found that the first few emotional modes accounted for the majority of variance, suggesting these represent the most fundamental narrative structures
- Synthetic "nonsense" texts lacked the coherent emotional arcs observed in the real stories, indicating the identified patterns reflect meaningful structures in how authors construct narratives
Summaries
21 word summary
Identified six core narrative arcs in over 1,700 books, observing genre and cultural differences with applications in creative writing and analysis.
44 word summary
This study identified six core narrative arcs in over 1,700 books, suggesting fundamental structures in storytelling. Certain arcs, like "Icarus" and "Oedipus," were more popular. The researchers observed genre and cultural differences, with potential applications in creative writing, literary analysis, and automated story generation.
119 word summary
This study analyzed the emotional trajectories of over 1,700 books, identifying six core narrative arcs: "Rags to Riches," "Tragedy," "Man in a Hole," "Icarus," "Cinderella," and "Oedipus." These arcs were found across genres, suggesting they are fundamental to storytelling. Certain arcs, like "Icarus" and "Oedipus," were associated with more popular stories. The researchers also observed genre and cultural differences, with romance novels often following the "Cinderella" pattern and American stories tending to have more positive emotional trajectories. This quantitative approach provides insights into the structures underlying compelling narratives, with potential applications in creative writing, literary analysis, and automated story generation. Further research is needed to explore the relationship between emotional arcs and other narrative elements across diverse cultural contexts.
386 word summary
This study examines the emotional arcs of stories by analyzing the sentiment trajectories of over 1,700 books from Project Gutenberg. The researchers used computational techniques to identify six core emotional arcs that capture the majority of variation in the data:
1. "Rags to Riches" (rise): A steady, positive emotional trajectory where the protagonist experiences an upward journey.
2. "Tragedy" or "Riches to Rags" (fall): A steady, negative emotional trajectory where the protagonist experiences a downward spiral.
3. "Man in a Hole" (fall-rise): An initial emotional decline followed by a recovery and rise.
4. "Icarus" (rise-fall): An initial ascent in emotional positivity followed by a dramatic plunge.
5. "Cinderella" (rise-fall-rise): A narrative arc with an emotional roller coaster of an initial rise, a fall, and then a final rise.
6. "Oedipus" (fall-rise-fall): A narrative with a reversal in emotional trajectory, starting with a decline, then a rise, and finally another fall.
The researchers found that these core emotional arcs were consistently present across diverse literary genres, suggesting they represent fundamental building blocks of compelling storytelling. Further analysis revealed that certain emotional arcs, like "Icarus," "Oedipus," and sequential "Man in a Hole," were associated with more successful and popular stories as measured by download counts.
The study also uncovered interesting patterns in how emotional arcs vary by genre. For example, romance novels often followed the "Cinderella" pattern, while horror stories were more likely to exhibit the "Man in a Hole" arc. Additionally, the researchers observed cultural differences, with American stories tending to have more positive emotional trajectories compared to works from other regions.
By quantifying the emotional dynamics of stories, this research provides insights into the underlying structures and patterns that shape the narrative experiences of readers. The findings have potential applications in areas like creative writing, literary analysis, and even automated story generation. Understanding the common emotional arcs that resonate with audiences can inform the design of engaging narratives and interactive experiences.
The researchers note that further work is needed to explore the relationship between emotional arcs and other narrative elements, as well as to extend the analysis to a broader range of literary genres and cultural contexts. Nevertheless, this study represents an important step in the computational study of literary emotion and narrative form, offering a data-driven framework for understanding the building blocks of compelling storytelling.
1663 word summary
The emotional arcs of stories are dominated by six basic shapes: "Rags to riches" (rise), "Tragedy" or "Riches to rags" (fall), "Man in a hole" (fall-rise), "Icarus" (rise-fall), "Cinderella" (rise-fall-rise), and "Oedipus" (fall-rise-fall). These core emotional arcs were identified through three independent methods: matrix decomposition, supervised learning, and unsupervised learning.
The researchers analyzed a corpus of 1,327 fiction books from Project Gutenberg, extracting the emotional content of each book using sentiment analysis. They found that the first four emotional arc modes captured the majority of the variance in the data, corresponding to the six core arcs. Further analysis showed that certain emotional arcs, like "Icarus", "Oedipus", and sequential "Man in a hole", were associated with more successful and popular stories as measured by downloads.
The researchers conclude that automated extraction of emotional arcs can provide new insights into the structure and patterns of stories, and that consideration of the emotional trajectory may be an important factor in the success and appeal of narratives. Their findings suggest universal building blocks of storytelling that resonate with readers.
This study examines the emotional arcs of stories by analyzing a large corpus of Project Gutenberg eBooks. The researchers used a sentiment analysis technique to classify the emotional tone of each book, represented by a sequence of sentiment values over the course of the narrative.
The data includes over 200 popular eBooks, ranked by download count, with information on the sentiment trajectory, word count, and unique word count for each work. The sentiment values range from -1 to 1, with higher values indicating more positive emotional content.
The analysis reveals diverse emotional patterns across the stories, with some following classic narrative arcs like "rags to riches" and others exhibiting more complex, nonlinear trajectories. The researchers also found correlations between the emotional arc and other textual features, such as word count and vocabulary diversity.
Overall, this study provides insights into the emotional dynamics of storytelling and demonstrates the potential of computational techniques to uncover patterns in large-scale literary datasets. The findings could inform our understanding of narrative structure and reader engagement, with applications in areas like creative writing, literary analysis, and recommendation systems.
The researchers note that further work is needed to explore the relationship between emotional arcs and other narrative elements, as well as to extend the analysis to a broader range of literary genres and cultural contexts. Nevertheless, this study represents an important step in the computational study of literary emotion and narrative form.
This study examines the emotional arcs of stories, analyzing a large corpus of Project Gutenberg eBooks to identify common narrative patterns. The researchers developed a novel computational model to quantify the emotional trajectories of stories, capturing key elements like rising action, climax, and resolution.
The analysis revealed several distinct emotional arcs that frequently occur across diverse literary genres. These include the "Rags to Riches" arc, characterized by an upward trajectory, and the "Tragedy" arc, marked by a downward emotional progression. Other common patterns include the "Man in a Hole" arc, with a dip followed by recovery, and the "Icarus" arc, featuring an initial ascent followed by a dramatic fall.
The researchers found that certain emotional arcs are more prevalent in specific genres. For example, "Rags to Riches" stories are common in romance and adventure fiction, while "Tragedy" arcs are more prevalent in literary fiction. The study also identified cultural differences, with American stories tending to have more positive emotional trajectories compared to those from other regions.
This work provides valuable insights into the underlying structures and patterns that shape the emotional experiences of readers. The findings have implications for understanding the psychology of storytelling, as well as potential applications in areas like narrative design and automated story generation. By revealing the common emotional arcs that resonate with audiences, this research offers a new lens for analyzing and crafting compelling narratives.
This study examines the emotional arcs of stories, analyzing over 1,700 books from Project Gutenberg. The researchers used a sentiment analysis technique to track the emotional trajectories of the narratives. They identified six common emotional arcs: rags-to-riches, tragedy, man-in-a-hole, Icarus, Cinderella, and Oedipus.
The most common arc was the "man-in-a-hole" pattern, where the protagonist experiences an initial fall followed by a rise. This was seen in over 30% of the books. The "Icarus" arc, with an initial ascent and then a plunge, was the next most frequent at around 7%.
Interestingly, the researchers found that the emotional arcs tended to cluster by genre. For example, romance novels often followed the "Cinderella" pattern of rising steadily, while horror stories were more likely to exhibit the "man-in-a-hole" arc. The study also revealed differences in emotional trajectories between popular and critically acclaimed works.
Overall, this research provides insights into the common narrative structures that resonate with readers and shape their emotional experiences. The findings could have applications in areas like creative writing, film, and even product design. By understanding these underlying patterns, storytellers and designers may be better equipped to craft engaging experiences that connect with their audiences on a deeper level.
The study examines the emotional arcs of stories by analyzing the sentiment trajectories of over 1,300 Project Gutenberg books. Using singular value decomposition (SVD), the authors identify six primary emotional modes that capture the majority of variation in the data. These modes correspond to common narrative structures like "Rags to Riches" and "Tragedy".
The authors find that the first three modes account for over 60% of the variance in the data, suggesting these represent the most fundamental emotional arcs. Subsequent modes capture more nuanced emotional patterns. For example, mode 4 corresponds to a "Icarus" arc of rising and falling, mode 5 to a "Man in a Hole" structure, and mode 6 to an "Oedipus" narrative of reversal.
By projecting each book's emotional trajectory onto these modes, the authors can quantify how well each story fits the different archetypal arcs. They find that bestselling and critically acclaimed books tend to be well-represented by the first few modes, while less popular works exhibit more complex, multi-modal emotional structures.
Overall, this study provides a data-driven framework for understanding the common emotional patterns underlying creative narratives. The results offer insights into the building blocks of compelling storytelling and have potential applications in areas like narrative generation and emotional design.
This study examines the emotional arcs of stories, analyzing how the sentiment or emotional tone changes over the course of a narrative. The researchers used a dataset of over 1,700 books from Project Gutenberg to identify common emotional trajectories.
Through singular value decomposition, the team extracted three core emotional arcs that capture the majority of variation in the data. The first arc represents a steady rise in positivity, the second a rise and fall in sentiment, and the third a more dramatic emotional roller coaster.
The authors then identified the stories that most closely match each of these core arcs, providing detailed lists sorted by the strength of the match and by download popularity. For example, the first arc is strongly represented by classics like "The Jungle Book" and "Tarzan of the Apes", while the second arc includes works like "The Picture of Dorian Gray" and "Beowulf".
By mapping these common emotional patterns, the researchers aim to provide a framework for understanding the structure and appeal of stories. The results could inform creative writing, narrative analysis, and even the design of interactive experiences. Overall, this work offers a quantitative perspective on the emotional dynamics that captivate readers and shape the timeless appeal of great stories.
The study examines the emotional arcs of stories, identifying seven core emotional trajectories that can capture the narrative structure of a wide range of literary works. The authors analyze a dataset of over 1,700 books, extracting features that describe the emotional dynamics within each story.
Through unsupervised learning, they discover the seven dominant emotional arcs: rags-to-riches, tragedy, man-in-a-hole, Icarus, Cinderella, Oedipus, and Man-in-a-hole. These patterns reflect common narrative structures found across diverse genres, from classic novels to modern science fiction.
The researchers then rank stories based on how well their emotional arcs align with each of the seven core arcs. This allows them to identify the stories that most strongly exemplify each emotional trajectory. For example, "The Adventures of Tom Sawyer" and "Peter Pan" are among the stories that best fit the Icarus arc, while "Northanger Abbey" and "Ethan Frome" capture the tragedy arc.
By mapping the emotional dynamics of stories, the study provides a framework for understanding the underlying structure of narratives. This has implications for fields like literary analysis, screenwriting, and even artificial intelligence systems that generate creative content. The findings suggest that while stories may vary greatly in their specific details, they often follow a limited set of recognizable emotional patterns that resonate with readers and audiences.
The study examined the emotional arcs of stories, analyzing a dataset of over 1,700 books from Project Gutenberg. The authors identified 6 core emotional arcs that account for a significant portion of the variance in the emotional trajectories of these stories.
The core arcs include: 1) a steady, positive emotional trajectory; 2) a steady, negative trajectory; 3) a rise-fall pattern; 4) a fall-rise pattern; 5) a fall-rise-fall pattern; and 6) a rise-fall-rise pattern. These core arcs were found to represent the emotional journeys of many popular and classic works of fiction.
To test the significance of these findings, the authors generated "nonsense" and "word salad" versions of the stories by using Markov models and random word shuffling. The emotional arcs of these synthetic texts lacked the coherent structure observed in the real stories, with the SVD, clustering, and SOM analyses revealing more diffuse and less interpretable patterns.
This suggests that the identified core emotional arcs are not simply an artifact of the data or analysis methods, but rather reflect meaningful patterns in how authors construct the emotional experiences of their characters and narratives. The study provides insights into the common emotional trajectories that resonate with readers and underlie the narrative structure of impactful stories.