The emotional arcs of stories are dominated by six basic shapes
The emotional arcs of stories are dominated by six basic shapes
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DOI：
10.1140/epjds/s13688-016-0093-1
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发表时间：
2016-11-04
期刊：
影响因子：
3.6
通讯作者：
Dodds, Peter Sheridan
中科院分区：
文献类型：
--
作者：
Reagan, Andrew J.;Mitchell, Lewis;Dodds, Peter Sheridan
现在，计算能力，自然语言处理和文本数字化的进步使得通过使用“大数据”镜头通过文化的文化发展成为可能。我们交流的能力部分取决于共同的情感体验，故事通常遵循截然不同的情感轨迹和形成对我们有意义的模式。在这里，通过对Gutenberg Project的小说系列中的1,327个故事的过滤子集进行分类，我们找到了一组六个核心情感弧，构成了复杂的情感轨迹的基本基础。我们通过单独应用矩阵分解，监督学习和无监督学习来加强我们的发现。对于这六个核心情感弧线中的每一个，我们都会研究当今出版物中最接近的特征故事，并发现特定的情感弧线取得了更大的成功，如下载所衡量。
Advances in computing power, natural language processing, and digitization of text now make it possible to study a culture's evolution through its texts using a 'big data' lens. Our ability to communicate relies in part upon a shared emotional experience, with stories often following distinct emotional trajectories and forming patterns that are meaningful to us. Here, by classifying the emotional arcs for a filtered subset of 1,327 stories from Project Gutenberg's fiction collection, we find a set of six core emotional arcs which form the essential building blocks of complex emotional trajectories. We strengthen our findings by separately applying matrix decomposition, supervised learning, and unsupervised learning. For each of these six core emotional arcs, we examine the closest characteristic stories in publication today and find that particular emotional arcs enjoy greater success, as measured by downloads.