Case (![[personal profile]](https://www.dreamwidth.org/img/silk/identity/user.png)
case) wrote in ![[community profile]](https://www.dreamwidth.org/img/silk/identity/community.png)
fandomsecrets2014-01-30 06:43 pm
case) wrote in fandomsecrets2014-01-30 06:43 pm
[ SECRET POST #2585 ]
⌈ Secret Post #2585 ⌋
Warning: Some secrets are NOT worksafe and may contain SPOILERS.
01.
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02.
[Monster High]
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03.
[Bryan Fuller, John Green]
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04.
[Star Trek: The Next Generation]
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05.
[Pretty Little Liars]
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06.
[Breaking Bad]
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07.
[Shin Megami Tensei: Strange Journey]
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08.
[Reign]
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09.
[Leviathan: the last day of the decade]
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10.
[Sherlock Holmes]
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11.
[Steam]
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12.
Notes:
Secrets Left to Post: 01 pages, 017 secrets from Secret Submission Post #369.
Secrets Not Posted: [ 0 - broken links ], [ 0 - not!secrets ], [ 0 - not!fandom ], [ 0 - too big ], [ 0 - repeat ].
Current Secret Submissions Post: here.
Suggestions, comments, and concerns should go here.
Re: OP
I would like to write a program that can detect from linguistic data, such as frequency of common words, length of words, length of sequences, variety of vocabulary etc. whether a piece of fiction is more likely to be idea-driven, action-driven or character-driven.
My current attempts were to the avail of using the source code of the popular I Write Like site in order to detect some patterns,but I do not know whether the authors there are really representative for the genres in question.
Maybe I need to select my own corpus and use it to train an analyser bot. Have you got some suggestion which works archived in Gutenberg's Project look most representative? Alas, I fear that, as those works would have to be very old in order to be used legally, my results would reflect a long-since gone state of the art instead of contemporary fiction; but copyright is as it is.