Nabokov's Favorite Word Is Mauve

Nabokov's Favorite Word Is Mauve pdf epub mobi txt 电子书 下载 2025

Ben Blatt is a former staff writer for Slate and The Harvard Lampoon who has taken his fun approach to data journalism to topics such as Seinfeld, mapmaking, The Beatles, and Jeopardy! His previous book, co-written with Eric Brewster, is I Don't Care if We Never Get Back, which follows the duo’s quest to go on the mathematically optimal baseball road trip, traveling 20,000 miles to a game in all thirty ballparks in thirty days without planes. Blatt’s work has also been published in The Wall Street Journal, The Boston Globe, and Deadspin.

出版者:Simon & Schuster
作者:Ben Blatt
出品人:
页数:288
译者:
出版时间:2017-3-14
价格:USD 25.00
装帧:Hardcover
isbn号码:9781501105388
丛书系列:
图书标签:
  • 数据分析 
  • 文学 
  • 非虚构 
  • 英文 
  • 美国 
  • 写作 
  • Books-About-Books 
  • 文化 
  •  
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There’s a famous piece of writing advice—offered by Ernest Hemingway, Stephen King, and myriad writers in between—not to use -ly adverbs like “quickly” or “fitfully.” It sounds like solid advice, but can we actually test it? If we were to count all the -ly adverbs these authors used in their careers, do they follow their own advice compared to other celebrated authors? What’s more, do great books in general—the classics and the bestsellers—share this trait?

In Nabokov’s Favorite Word Is Mauve, statistician and journalist Ben Blatt brings big data to the literary canon, exploring the wealth of fun findings that remain hidden in the works of the world’s greatest writers. He assembles a database of thousands of books and hundreds of millions of words, and starts asking the questions that have intrigued curious word nerds and book lovers for generations: What are our favorite authors’ favorite words? Do men and women write differently? Are bestsellers getting dumber over time? Which bestselling writer uses the most clichés? What makes a great opening sentence? How can we judge a book by its cover? And which writerly advice is worth following or ignoring?

Blatt draws upon existing analysis techniques and invents some of his own. All of his investigations and experiments are original, conducted himself, and no math knowledge is needed to understand the results. Blatt breaks his findings down into lucid, humorous language and clear and compelling visuals. This eye-opening book will provide you with a new appreciation for your favorite authors and a fresh perspective on your own writing, illuminating both the patterns that hold great prose together and the brilliant flourishes that make it unforgettable.

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谁能帮我们找到《洛丽塔》的作者纳博科夫最喜欢的词?纳博科夫自己,狂热读者书迷,他的传记作者,亦或文学评论家?结果是——统计学家。这可能有点出乎意料,但细想之下又在情理之中。用计算机爬梳一下纳博科夫所有的作品,找出几个“高频词”似乎并非么难事,为何值得专门写...  

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第七章特别有意思,感觉这个feature engineering做起来会很好玩

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非常有趣;不只是将纳博科夫的,主要对多种文学作品内容的词频分析,有很多有趣的结论。

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蛮有意思的数据分析,讲了作者是不是遵循自己提出的写作技巧(例如少用副词,简练、简短开头等等),用词和POV上的性别差异,写作的音量,封面营销(随着作家名气渐长,名字占封面比越来越大),以及随着时代发展文学作品变得越来越通俗易懂。读过之后更令我感觉名作者果真是厉害。。。

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引人入胜,两天一气儿读完。很欣赏作者对分析结果谨慎谦虚的解读。如果说像FiveThirtyEight类似的分析是带点功利主义的,但对文学用数据的解读不太可能是为了reverse-engineer出最好的写作模式,看喜欢的作家们好像被排成一排检视一番看说没说真话确实是种新奇有趣的体验

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为被嫌弃的同人作者默哀一分钟……美国人写作“也很大声”这个例子让人终生难忘

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