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dariusk
NaNoGenMo-2015
OPEN SOURCE2015–2019
dariusk / NaNoGenMo-2015

NaNoGenMo-2015

National Novel Generation Month, 2015 edition.

7Distinct people
8Mentions
0Explicit recommenders
340GitHub stars
REPOSITORY AT A GLANCE

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What it is

National Novel Generation Month, 2015 edition.

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This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year8 dated mentions

Observed mentions: 2015-10-26 14:12:35 UTC to 2019-11-11 17:46:17 UTC.

02462015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 6 mentions; 5 submissions, 1 comments20152016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20172018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2019

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC651
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC101
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC000
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC000
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC101

What Hacker News says

8 sources
A few days ago I discovered this initiative that I found very interesting and fun: during the month on November you have to develop a program to generate a novel of around 50k words. This is the 7th edition of the event. I started reading the dev-logs (GitHub issues) of the past editions and discovered some great novels both in term of technology involved and also content. Some gems: * MARYSUE (https://github.com/catseye/MARYSUE), which aims to create an interesting novel with a plot and everything else (and the related write-up "A story compiler" (https://git.catseye.tc/MARYSUE/blob/master/doc/Overview%20of...) * LIFE OF THE AZAR (https://github.com/NaNoGenMo/2017/issues/39), an archive/enciclopedia of some sort of an imaginary city of a couple of thousands of citizens describing the people, their relationships, events that happens in th
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e city and much more * THE DESERT OF THE WEST (https://github.com/dariusk/NaNoGenMo-2015/issues/156), a generated guide of imaginary worlds together with a map generation alghoritm with rivers and erosion (http://mewo2.com/notes/terrain/) and a generator for city names based on natural language theories (http://mewo2.com/notes/naming-language/) * MEOW (https://github.com/dariusk/NaNoGenMo-2014/issues/50) meow meow meeeooow mew Some projects are based on Neural Networks, some on Markov Chains, some on simulations, some on Tracery grammars (https://tracery.io/), some on Prolog, some on "plain" text processing and some on a mix of all of these. (I found an overview of the approaches for the 2016 edition here https://github.com/NaNoGenMo/2016/issues/154) I find all of this very fascinating and might start my own adventure with text generation in the next days.
In NaNoGenMo - Spend the month of November writing code that generates a novel
To my knowledge, no such program exist, but each of the stuff you mentioned has been done before. INPUT Quick character description - Users specify some character traits to be associated with a character. The program then will pick words associated with that trait to be used with that character. Words could be pithy sayings, actions, or even adjectives. https://github.com/tra38/Skynet (Disclaimer: I wrote this as part of my original attempt at narrative generation, but the results was panned. Handling character descriptions was one of the highlights...in the sense readers never complained about my characters. At the same time, people never seemed to noticed or cared about the characterization at all, so it's possible that this approach may have been unnecessary and a less heavyweight solution should be preferred.) Setting - When writing t
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he story templates the computer will end up using to generate the story, set aside some spaces for describing the setting. You could attempt to just plug in just the name of the setting ("EwanG's Glorious Emporium") into those blanks, or maybe you could have the computer look up information in a database such as Wikipedia or WordNet to give it more flavor. This approach was used in the computer-generated novel "Around the World In X Wikipedia Articles" that uses Wikipedia to describe its settings (https://github.com/dariusk/NaNoGenMo-2015/issues/142) and in a series of simulations fantasy novels that uses WordNet to describe its settings (https://github.com/dariusk/NaNoGenMo-2015/issues/40). Alternatively, you could generate descriptive and evocative phrases associated with your setting name. This can add more flavor to your story. (This was done in the computer-generated novel "Our Arrival": https://github.com/dariusk/NaNoGenMo-2015/issues/25) General Outline Of The Story - The 'story compiler' approach, invented by Chris Pressey, starts off with a "null story" (characters meet each other and then characters leaves). The compute starts filling in the outline by adding in plots to this "null story", but each plot has a wildcard that can allow for plots to be nested within plots. After it finishes adding plots to the story, it then goes through each scene of the story and then "flesh" it out. The Story Compiler approach was used to generate "A Time of Destiny". Here's an issue that gives you links to the theory, the code, and the actual novel: https://github.com/dariusk/NaNoGenMo-2015/issues/11 Now, you want to specify the plot, not let the computer randomly decide, so you may want to skip the first few steps, while instead focusing on having the program handle your unique array of scenes. This is going to be the hardest part of your program (writing up the different plots and all the individual scenes within each plot). And you don't want to write up too many plots, because then it will be seen as you writing your stories, not necessarily the computer. You could have plots reuse different scenes to reduce your workload. OUTPUT Output of Couple Hundred Pages - Every year, programmers all around the world attempt to participate in National Novel Generation Month, where the goal is to generate 50,000 words. This is both a very easy problem (set the program up in a loop until you get over 50,000 words) and a very hard problem (once people see the pattern within the generated story, they will get bored pretty fast and stop reading...or even skimming...how do you prevent readers from getting bored when reading the novel?). Still, if you can build a program that can handle one of your arbitrary input, then you can build a program to handle hundreds of arbitrary inputs. Whether you want to read all of the resulting outputs however is a different question...but then you're planning on 'lightly' editing the output, right? Maybe it might work. Every link that I gave you was an entry in the latest NaNoGenMo competition (https://github.com/dariusk/NaNoGenMo-2015), with the exception of the Skynet link that I gave you. Skynet, however, was intended to be be used in an entry in that competition. ==== So yeah, what you say is doable, and can be done. If you want to take this as a challenge to produce your own lovely program to generate your 85 wonderful stories, go right to it. (Or just find somebody's novel generator and just modify that to produce your lovely 85 stories). But don't limit yourself to conventional understanding of stories. For example, one of my actual entries to NaNoGenMo involve randomly shuffling the paragraphs of an article, thereby generating a brand new article (https://github.com/dariusk/NaNoGenMo-2015/issues/180). The result was rather surprisingly effective, and I ended up using this similar approach in generating a blog post (https://gist.github.com/tra38/8a6bf3743cd89687151c) and a short story (https://gist.github.com/tra38/02b03745e7da37789ed2). Experimentation can lead to new insights, especially about creativity.
In An A.I. Competed for a Literary Prize, but Humans Still Did the Real Work

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