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The second blog post of the set, comparing social network density (E/V^2) in tragedies and comedies: [http://axiomofcats.com/2012/08/30/social-networks-of-shakespearean-plays-part-2/].
The second blog post of the set, comparing social network density (E/V^2) in tragedies and comedies: [http://axiomofcats.com/2012/08/30/social-networks-of-shakespearean-plays-part-2/].
They make a cute observation that these networks are highly connected in Act 5 when the play is a comedy, which often end in weddings (and thus high co-occurrence).
They make a cute observation that these networks are highly connected in Act 5 when the play is a comedy, which often end in weddings (and thus high co-occurrence).
==Possible and previously discussed project directions==
A non-exclusive, non-exhaustive and otherwise rough list of ideas that have come up recently. We could use this page to structure some of our results or sub-projects (see next section).
Predicting tragedy/comedy(/history)
Gender
Gender and character roles
Dynamics of the network(s)
Probabilistic modeling of the networks (consider also tragedy/comedy, gender, dynamics and evolution, etc.)
Language in Shakespeare (consider also tragedy, gender, dynamics, etc.) - more here.
Hierarchical/social roles in Shakespeare
Story structure in Shakespeare
Narrative style and structure (focus on main characters vs. more contextual/observed scenes)
etc.
==Possible uses for this page==
Structuring or collecting results
Collecting information about the data or code
Sharing analyses
Nothing after this week
Showing off our results at the end of the summer school
etc.

Revision as of 22:00, 6 June 2013

Project page for A Midsummer Night's Project: Comedy and Tragedy in Shakespeare

Previous project description here: [1].

Data and code currently in the Dropbox folder.


Related work and links

There have been a few informal explorations of this so far that I've found.

There are a set of animations of the dynamics of communication in Shakespeare plays [2] , using PieSpy [3], a heuristic-based tool to infer social networks from IRC. There isn't any analysis here and the data isn't available, but we could check out PieSpy's rules for inferring relationships. (Our methods so far: co-occurrence and before- and after- speaking turns; easy next steps could use weighted co-occurrence--as in the next set of blog posts--and longer-memory speaking turns.)

Set of blog posts using co-occurrence to construct social networks in Shakespeare, starting here: [4]. These are co-occurrence networks, where co-occurrences is measured within scenes, and the networks are broken down by acts. Edges are weighted (and sometimes thresholded) by the number of scenes with dyad co-occurrence. They point out that you can start to see the plot of the Tempest, though I think our networks showed that more clearly.

The second blog post of the set, comparing social network density (E/V^2) in tragedies and comedies: [5]. They make a cute observation that these networks are highly connected in Act 5 when the play is a comedy, which often end in weddings (and thus high co-occurrence).


Possible and previously discussed project directions

A non-exclusive, non-exhaustive and otherwise rough list of ideas that have come up recently. We could use this page to structure some of our results or sub-projects (see next section).


Predicting tragedy/comedy(/history)

Gender

Gender and character roles

Dynamics of the network(s)

Probabilistic modeling of the networks (consider also tragedy/comedy, gender, dynamics and evolution, etc.)

Language in Shakespeare (consider also tragedy, gender, dynamics, etc.) - more here.

Hierarchical/social roles in Shakespeare

Story structure in Shakespeare

Narrative style and structure (focus on main characters vs. more contextual/observed scenes)

etc.


Possible uses for this page

Structuring or collecting results

Collecting information about the data or code

Sharing analyses

Nothing after this week

Showing off our results at the end of the summer school

etc.