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Nabokov's Favorite Word Is Mauve: what the numbers reveal about the classics, bestsellers, and our own writing
(eAudiobook)

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Published:
[United States] : Tantor Media, Inc., 2017.
Content Description:
1 online resource (1 audio file (5hr., 24 min.)) : digital.
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Description

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 cliches? 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. 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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Format:
eAudiobook
Edition:
Unabridged.
Language:
English
ISBN:
9781541428065, 1541428064

Notes

Restrictions on Access
Instant title available through hoopla.
Participants/Performers
Read by Vikas Adam.
Description
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 cliches? 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. 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.
System Details
Mode of access: World Wide Web.

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Citations

APA Citation (style guide)

Blatt, B., & Adam, V. (2017). Nabokov's Favorite Word Is Mauve: what the numbers reveal about the classics, bestsellers, and our own writing. Unabridged. [United States], Tantor Media, Inc.

Chicago / Turabian - Author Date Citation (style guide)

Blatt, Ben and Vikas, Adam. 2017. Nabokov's Favorite Word Is Mauve: What the Numbers Reveal About the Classics, Bestsellers, and Our Own Writing. [United States], Tantor Media, Inc.

Chicago / Turabian - Humanities Citation (style guide)

Blatt, Ben and Vikas, Adam, Nabokov's Favorite Word Is Mauve: What the Numbers Reveal About the Classics, Bestsellers, and Our Own Writing. [United States], Tantor Media, Inc, 2017.

MLA Citation (style guide)

Blatt, Ben, and Vikas Adam. Nabokov's Favorite Word Is Mauve: What the Numbers Reveal About the Classics, Bestsellers, and Our Own Writing. Unabridged. [United States], Tantor Media, Inc, 2017.

Note! Citation formats are based on standards as of July 2022. Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy.

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Grouped Work ID:
48d69329-9835-02f4-b481-62967bbce2fa
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Hoopla Extract Information

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