Technology Review<\/a> reports on research by computer scientist Andrew Reagan of the University of Vermont that uses data-mining to determine the most common story-arcs of 1700 English stories and novels. Their method is: \u201cwords have a positive or negative emotional impact. So words can be a measure of the emotional valence of the text and how it changes from moment to moment. So measuring the shape of the story arc is simply a question of assessing the emotional polarity of a story at each instant and how it changes. Reagan and co do this by analyzing the emotional polarity of \u2018word windows\u2019 and sliding these windows through the text to build up a picture of how the emotional valence changes.\u201d<\/p>\nTheir discovery: \u201cWe find a set of six core trajectories which form the building blocks of complex narratives.\u201d According to the MIT summary, these are: \u201cA steady, ongoing rise in emotional valence, as in a rags-to-riches story such as Alice\u2019s Adventures Underground by Lewis Carroll. A steady ongoing fall in emotional valence, as in a tragedy such as Romeo and Juliet. A fall then a rise, such as the man-in-a-hole story, discussed by Vonnegut. A rise then a fall, such as the Greek myth of Icarus. Rise-fall-rise, such as Cinderella. Fall-rise-fall, such as Oedipus. . . . the most popular are stories that follow the Icarus and Oedipus arcs and stories that follow more complex arcs that use the basic building blocks in sequence.\u201d<\/p>\n
This is hardly the end of research on the topic: \u201cReagan and co look mainly at works of fiction in English. It would be interesting to see how emotional arcs vary according to language or culture, how they have varied over time and also how factual books compare.\u201d<\/p>\n
(Thanks to Tim Varner for passing on the link.)<\/p>\n<\/body><\/html>\n","protected":false},"excerpt":{"rendered":"
MIT\u2019s Technology Review reports on research by computer scientist Andrew Reagan of the University of Vermont that uses data-mining to determine the most common story-arcs of 1700 English stories and novels. Their method is: \u201cwords have a positive or negative emotional impact. So words can be a measure of the emotional valence of the text […]<\/p>\n","protected":false},"author":3021,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[874,432,1653],"tags":[],"class_list":["post-18329","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-literary-structure","category-plot"],"yoast_head":"\n
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