Dear Aaron, 

sorry, sorry, thanks for helping clear up some mis-conceptions, and let me see if I can do more. 

The WikiWho API is very nice work, and was presented in WWW 2014. 

The work of Michael and myself dates from one year before, WWW 2013 (see http://www2013.wwwconference.org/proceedings/p343.pdf).  

This is why in our work we don't give credit to WikiWho.  In fact, it is them who most politely cite us. 

Now, you say, why don't I give them more credit now?  Because I haven't really done anything new.  I am not claiming anything new, I have just taken code that was written in 2013, and made it better available on github, with a moderate clean-up of its API.  We tried to make that code available in 2013 to the community, by putting it into gerritt (we were told it was the proper place), but it didn't really work out.  Again, I am not pushing a new result out.  I am simply making code available that dates from some time back, and that I realized yesterday might be useful to others. 

There are many many ways to attribute content.  Even if you go for the theory of "earliest possible attribution", which is what we do in the paper and code, it would certainly be better done using language models of average text, to better distinguish casual from intentional repetition. 

I put the code on github because I was inspired by our conversation yesterday.  If you like, I'd be happy to give you access to the repo (write access I mean) so you can both do the code reviews we had been mentioning, and improve the README.md file with more considerations and references.  Let me know. 

Again, what I wanted to do is make better available code written 2-3 years ago, not really make any new claims. 

Luca




On Fri, Aug 21, 2015 at 5:49 PM, Aaron Halfaker <aaron.halfaker@gmail.com> wrote:

Hey Luca!

Welcome back to the content persistence tracking club! 

I feel like I should clear up some misconceptions.  1st, yours is not the first python library that is useful for determining the authorship of content in versioned text and I don't think you have given fair treatment to the work we have been doing since you last worked on WikiTrust.  For example, its hard to tell from your description whether you are doing anything different than the wikiwho api[2] with tracking content historically.  Further the work I have been doing with diff-based content persistence (e.g. [1]) is not so simple as to not notice removals and re-additions under most circumstances.

In my opinion, this is much better for measuring the productivity of a contribution (adding content that looks like content that was removed long ago is still productive, isn't it?), but maybe less useful for attributing a first contributor status to a particular sub-statement.  Regardless, it seems that a qualitative analysis is necessary to determine whether these differences matter and whether one strategy is better than the other.  AFAICT, the only software that has received this kind of analysis is wikiwho (discussed in [3]).

Regardless, it's great to have you working in this space again and I welcome you to help us develop overview of content persistence measurement strategies that is complete and allows others to critically decide which strategy matches their needs.   See https://meta.wikimedia.org/wiki/Research:Content_persistence for such an overview.  I encourage you to use this description of persistence measures to differentiate your strategy from the work we have been doing over the last 5 years.  Edit boldly!

1. https://pythonhosted.org/mediawiki-utilities/lib/persistence.html#mw-lib-persistence
2. http://people.aifb.kit.edu/ffl/wikiwho/
3. http://people.aifb.kit.edu/ffl/wikiwho/fp715-floeck.pdf

-Aaron


On Aug 21, 2015 4:52 PM, "Luca de Alfaro" <luca@dealfaro.com> wrote:
Dear All, 

I was yesterday at OpenSym (many thanks to Dirk for organizing this!), and I was chatting with some people about attribution of content to its authors in a wiki. 
So I got inspired, and I cleaned up some code that Michael Shavlovsky and I had written for this:


The way to use it is super simple (see below).  The attribution object can also be serialized and de-serialized to/from json (see documentation on github). 

The idea behind the code is to attribute the content to the earliest revision where the content was inserted, not the latest as diff tools usually do.  So if some piece of text is inserted, then deleted, then re-inserted (in a revert or a normal edit), we still attribute it to the earliest revision.  This is somewhat similar to what we tried to do in WikiTrust, but it's better done, and far more efficient.

The algorithm details can be found in http://www2013.wwwconference.org/proceedings/p343.pdf

I hope this might be of interest! 

Luca
import authorship_attribution

a = authorship_attribution.AuthorshipAttribution.new_attribution_processor(N=4)
a.add_revision("I like to eat pasta".split(), revision_info="rev0")
a.add_revision("I like to eat pasta with tomato sauce".split(), revision_info="rev1")
a.add_revision("I like to eat rice with tomato sauce".split(), revision_info="rev3")
print a.get_attribution()
['rev0', 'rev0', 'rev0', 'rev0', 'rev3', 'rev1', 'rev1', 'rev1']

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