If you're ever reading a book or watching a movie and get the distinct feeling you've come across the story before – or even better, can predict exactly what's going to happen next –there could be a good reason for that.

　　如果你在读书或者看电影时清晰地感觉到这个故事似曾相识——或者更厉害的，你能准确预测出后面会发生些什么——嗯，这种感觉可不是毫无依据的。

　　Computer scientists have sifted through the language of more than 1,700 works of fiction and discovered that English literature consists of just six kinds of emotional arcs that make up nearly all of the most well-known stories.

　　计算机科学家们在测查了1700多部小说后，发现英语文学中只包含六种情感弧线，而几乎所有的名著都是由它们构成的。

　　While literary theorists have for centuries characterised and counted the basic plots and structures that writers use in stories, it's unlikely there's ever been such a rigorous scientific analysis of English fiction like this before.

　　尽管若干世纪以来，文学理论家们一直在研究作家写故事时应用的基本情节和结构，分析它们的特征，历数其种类，但好像此前从来没有针对英语小说做过如此严谨的科学分析。

　　Researchers from the Computational Story Laboratory at the University of Vermont mined the complete text of some 1,737 fiction works available on Project Gutenberg, an online collection of more than 50,000 digital books in the public domain. By analysing the sentiment of language used in chunks of text 10,000 words long in each of these texts, the researchers were able to register the emotional ups and downs for the stories as a whole. Negative words like "poverty", "dead", and "punishment" dragged the sentiment down, while positive terms like "love", "peace", and "friend" brought it up.

　　佛蒙特大学“计算机故事实验室”的研究员们从古登堡计划(Project Gutenberg是一个线上书库，内含5万多本公版电子书)上找到了大约1737部全文小说，他们将这些文本分成文本块，每个文本块包含1万个单词，然后分析其中的语言情感，最终得出故事整体的情感起伏。“贫穷”、“死亡”、“惩罚”等消极词汇会使情感变得低落，而“爱情”、“和平”、“友谊”之类积极词汇会使情感变得高昂。

　　Doing this for over 1,700 books and charting the dynamics of each text, the team discovered that all stories basically boil down to one of a set number of emotional patterns. "We find a set of six core trajectories which form the building blocks of complex narratives," the authors write in their study.

　　研究团队在按照这种方法将1700多本书逐本分析、并画出每本书的动态曲线图之后，他们发现所有的故事最后基本上都会归结到几种情感模式中的一种。研究报告中写道：“我们发现有6种核心的情感轨迹，它们是构成复杂叙事大厦的砖瓦。”

　　According to the researchers, those six core emotional arcs are:

　　根据研究人员的说法，这6种核心情感弧线包括：

　　· "Rags to riches" (An ongoing emotional rise, eg. Alice's Adventures Under Ground)

　　“白手起家型”(持续的情感上涨，如《爱丽丝地下奇遇记》)

　　· "Tragedy, or riches to rags" (An ongoing emotional fall, eg. Romeo and Juliet)

　　“悲剧型”或者“家道中落型”(持续的情感下落，如《罗密欧与朱丽叶》)

　　· "Man in a hole" (A fall followed by a rise)

　　“穴人型”(先下落后上涨)

　　· "Icarus" (A rise followed by a fall)

　　“伊卡洛斯型”(先上涨后下落)

　　· "Cinderella" (Rise–fall–rise)

　　“灰姑娘型”(上涨-下落-上涨)

　　· "Oedipus" (Fall–rise–fall)

　　“俄狄浦斯型”(下落-上涨-下落)

　　Interestingly, based on download statistics from Project Gutenberg, the researchers say the most popular stories are ones that use more complex emotional arcs, with the Cinderella and Oedipus arcs registering the most downloads. Also popular are works that combine these core arcs together in new ways within one story, such as two sequential "Man in a hole" arcs stuck together, or the "Cinderella" arc coupled with a tragic ending.

　　有趣的是，研究人员说：根据从古登堡计划下载的数据来看，最受欢迎的故事往往应用了较为复杂的情感弧线，“灰姑娘型”和“俄狄浦斯型”囊括了大多数下载作品。另外，还有一些很受欢迎的作品是以一种新的方式将几种情感弧线结合在一个故事里，比如说连续出现两个“穴人型”，或者在“灰姑娘型”后面加上一个悲剧结尾。