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Question: Is there a resource that categorizes existing fiction works by themes based on the authors' demographics (e.g. gender, age, historical period, geographical location, etc...)?

For instance, I was curious to determine whether statements like the following ones are true or false:

  • younger writers tend to be over-represented in fantasy rather than drama;
  • authors with scientific background write more science-fiction;
  • women's writings include more pregnancies compared to men's;
  • NorthAmerican writers use more guns/armed threats in their fiction compared to Brits and Scandinavians.
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    I know that some university library databases allow you to sort entries by author's gender, period, location, and so on - I believe you'd have to compile a database of your own to be able to find the statistics on things like pregnancies and guns. – tryin Jun 18 '19 at 10:34
  • However, using those resources to compile OP's own database for determining their answers wouldn't be too difficult, but would require the use of software like SPSS that not everyone has access to. – J Crosby Jul 24 '19 at 16:14
  • OCLC does provide an open RESTful API that can be accessed (sample code included) to pull data. VIAF also offers data dumps for download, but they are massive datasets (the XML dump is 14.4 GB). – Soulis Jul 26 '19 at 21:40
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The closest I could find was The Gender Balance of The New York Times Best Seller list on The Pudding comparing gender to genre. It barely scratches the surface of what you're looking for, but includes their data sources (specifically the Virtual International Authority File and OCLC Classify) at the bottom of the article.

Like tryin commented, you'll still have to cobble the data together to get some of the information, but some of it should be straightforward. For example, the Virtual International Authority File and OCLC Classify can be used to determine gender (like the article did), current age, and age at publication of a work. This will probably cover cases like your first bullet point. The second bullet point might be possible with more data sources (maybe scraping Wikipedia author pages) that can tie degrees or academic history to an author as well. The third and fourth bullet point maybe more difficult, but the OCLC Classify data also includes FAST (Faceted Application of Subject Terminology) headings, which you might be able to pull data on terms such as "pregnancy" and "guns" out of as well.

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