
The emotional arcs of stories are dominated by six basic shapes - ehudla
http://arxiv.org/abs/1606.07772
======
klue07
Am I missing something? The result for the 6 main emotional arcs basically
enumerates all the possible permutations of rise and fall of length 1, 2, and
3 which seems pretty obvious.

Length 1: rise, fall

Length 2: rise-fall, fall-rise

Length 3: rise-fall-rise, fall-rise-fall (must be interchanging because for
example fall-fall-rise would probably just be considered fall-rise)

~~~
sago
I thought the same, and as per fovc's comment, below, I think what their
statistical analysis did was basically a coarse fourier transform.

In the Harry Potter example you can see that a higher frequency is very
significant. But the exact frequency is probably rather arbitrary from book to
book, whether there are ten peaks or five, say. So I'd imagine, over lots of
texts, any particular higher frequencies is less significant, leaving the
lowest modes to dominate, as you point out.

So overall, a rather uninspiring result, I felt.

Though if we're _both_ missing something, it would be good to know!

~~~
hbosch
A note some HNers might find tangentially interesting: in David Foster
Wallace's _Infinite Jest_ , Fourier transforms are a bedrock concept for the
titular entertainment, which is considered such a perfect piece of media that
it is lethally addictive. How nice it was to see this post about "shapes of
narrative" be compared to Fourier transforms for a IJ nerd!

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fovc
Read this quickly, but my immediate thought when I saw the PCA result vectors
was that they resembled the Fourier basis. Given a relatively slow-moving set
of signals (which I think these are, given the 10,000 word sliding window),
wouldn't you _expect_ the PCA to give you exactly this? In other words, what
is the null hypothesis here and is it rejected?

~~~
ggggtez
I think the idea is, of you compare short fiction to the Harry Potter graph,
most stories have simple emotional arcs, rather than complicated back and
forth. Though, if you limit the word length allowed... I wonder how they deal
with "it was the best of times. it was the worst of times"...

~~~
schoen
You could mess up pretty easily at a local level with missed negations. For
example, John Lennon's song "Imagine" invites people to envision a world
_without_ various things; if you assign negative sentiment to those things,
you might infer that the song overall had very negative affect. Or religious
prophecies about a future era in which people wouldn't have to suffer from
various afflictions.

~~~
mcguire
Jockers, in one of his posts, argues that it's less of a problem than you
might think because it's a local problem that just adds noise to the data.
Plus, his different sentiment analysis techniques seem to more-or-less agree.

On the other hand, he tells of showing a graph to his son, of a book his son
had read, and being told the graph was completely wrong for part of the book
---it turns out that part of the book was written from the antagonist's
viewpoint and the "emotional valence" was apparently inverted.

See one of the follow-ups to
[http://www.matthewjockers.net/2015/02/02/syuzhet/](http://www.matthewjockers.net/2015/02/02/syuzhet/).

~~~
schoen
The longer discussion is [http://www.matthewjockers.net/2015/03/04/some-
thoughts-on-an...](http://www.matthewjockers.net/2015/03/04/some-thoughts-on-
annies-thoughts-about-syuzhet/) (which gives examples of negation that
sentiment analysis packages miss, but then some empirical evidence that
analysis of sentiment in several literary works doesn't seem to be affected
very much by this issue).

The antagonist's viewpoint issue appeared in footnote 1 of
[http://www.matthewjockers.net/2015/02/25/the-rest-of-the-
sto...](http://www.matthewjockers.net/2015/02/25/the-rest-of-the-story/) and
it does seem like the sentiment analysis would clearly be backwards overall if
this kind of thing continued for most of a book. (An example might be if an
author depicted people enjoying themselves while committing horrible acts, and
used more individual words related to the enjoyment than to the acts.)

Thanks for the references.

~~~
schoen
> people enjoying themselves while committing horrible acts

Now I'm kind of curious about sentiment analysis of something like _Fight
Club_.

------
ominous
As expected, given the title, this[0] lecture by Vonnegut is mentioned in the
article.

[0]:
[https://www.youtube.com/watch?v=oP3c1h8v2ZQ](https://www.youtube.com/watch?v=oP3c1h8v2ZQ)

~~~
monk_e_boy
Do you have any more of these? Since reading Dan Harmons story structure I
have enjoyed American television a lot more.

[http://channel101.wikia.com/wiki/Story_Structure_101:_Super_...](http://channel101.wikia.com/wiki/Story_Structure_101:_Super_Basic_Shit)

~~~
proksoup
That linked series specifically and Dan Harmon's approach there is my favorite
approach to these topics.

I wanted to also share
[https://en.wikipedia.org/wiki/Monomyth](https://en.wikipedia.org/wiki/Monomyth)
Joseph Campbell's very similar work that I think Dan gives credit to somewhere
in that 101 series.

------
joeld42
This seemed interesting because I am working on visual story structure
diagramming software (looking for beta users btw), but I wasn't very impressed
with their results. Basically the only interesting conclusion I could see was
"stories need emotional movement", e.g. there were no examples where things
were happy or sad and continued at the same level throughout the events of the
story.

I couldn't tell if this could even identify the stories shape from their
sentiment graph -- e.g. if you fed it "Cinderella" could it identify the "Rags
to Riches" plot that they identify?

It would be neat to see if you could extract and identify plot points --
deaths, fights, breakups, betrayals, (maybe with some of those newfangled
neural network thinggies) and look for patterns there.

Still, it's encouraging to see people working on this. Maybe the results seem
basic because this field is still unstudied. I expect software tools for
storytelling to change a lot in the coming years with all the exciting new
work in natural language processing and machine learning.

------
mynegation
In the article they review several story plot taxonomies. Interesting that
they do not include the one according to Borges that he describes in "Four
cycles": (1) city sieged and defended (2) story of return (3) search (of
treasure) (4) sacrifice of a god. Probably not the most complete taxonomy, but
likely most dramatic one.

~~~
glup
(5) story plots that belong to the Emperor

~~~
mcguire
(6) those that tremble as if mad?

------
mcguire
Last year, Matthew Jockers, an English professor at the University of
Nebraska-Lincoln, had a series of blog posts on the subject[1]---I haven't
heard of any actual publications from the work---that was pretty interesting.

I haven't read this paper yet (this post is falling off HN too fast!) but his
technique was to use sentence-level sentiment analysis to get a time-varying
signal, rub a Fourier transform against it, cut off all but the lowest
frequencies, and returned it to the time domain to draw pretty pictures. He,
too, came up with six basic arcs, I think, probably for the same reason that
klue07 mentions but using statistics against a bunch of books.

There was a certain amount of press coverage at the time. The R package,
syuzhet, is available on github[2]. Also, you can look at my notes on playing
wiht syuzhet and R[3].

[1] Starting with
[http://www.matthewjockers.net/2015/02/02/syuzhet/](http://www.matthewjockers.net/2015/02/02/syuzhet/)

[2] [https://github.com/mjockers/syuzhet](https://github.com/mjockers/syuzhet)

[3] [http://maniagnosis.crsr.net/2015/08/exploring-
syuzhet.html](http://maniagnosis.crsr.net/2015/08/exploring-syuzhet.html)
[http://maniagnosis.crsr.net/2015/08/syuzhet-prodding-
frequen...](http://maniagnosis.crsr.net/2015/08/syuzhet-prodding-frequency-
domain.html)

------
stcredzero
I wonder if there is something like this applicable to pacing in video games?
I wonder if video games could be adaptively paced based on user input?

~~~
joeld42
Valve's "Left 4 Dead" had a system like this called the "AI director" that was
pretty well-received.

See the part about "Generate Dramatic Game Pacing"
[http://www.valvesoftware.com/publications/2009/ai_systems_of...](http://www.valvesoftware.com/publications/2009/ai_systems_of_l4d_mike_booth.pdf)

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6stringmerc
Interesting. Also reminds me of the Thomas Lennon & Robert Ben Garant
screenwriting guide (excellent) which posits there is one - only one -
blockbuster movie format, and it's most easily seen in _Die Hard_.

Introduce likeable character - get them stuck in trouble - get them unstuck.

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codezero
This is awfully fun, I never saw Rom-coms the same after I noticed the trend
of get together, break up, then get back together again (rise, fall, raise) in
this paper.

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tuhins
Good stuff! Great to see people working on this.

