Hi guys,

I just saw this thread. Great to see your interest in the topic revived, Luca!
Thanks to Aaron for pointing out the related work :)

some comments:

 For example, its hard to tell from your description whether you are doing 
anything different than the wikiwho api[2] with tracking content historically.

The technique that Luca and Michael’s algorithm (let’s call it A3)  uses is 
quite different from wikiwho and has other tuning parameters. While A3 is built 
on the idea of finding identifying identical tokens via a “rarity function” (in 
the original paper it was a 4-token-sequence of the same neighbors, if I recall 
correctly), wikiwho uses a hierarchical splitting into paragraphs, sentences 
and then tokens (with diffing in the last stage). wikiwho could still be 
refined by testing different splitting of the text instead of paragraph and 
sentences (and a different differ, cf. e.g. Aaron’s work), while A3 depends 
much on the defined rarity function to decide if a token is “the same” , which 
has not been explored yet to full potential afaik. (correct me if I’m wrong, 
Luca)

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.

FWIW wikiwho also tracks exactly when a token appeared, dissappeared and 
reappeared, including if it was a reintroduction, repeated delete, etc. We also 
added the calculation of relationships between revisions (and in aggregation: 
editors), which is the data used in the whoVIS visualization [1]. It’s all 
avaliable in the WikiwhoRelationships.py at [2]. The API, however, so far only 
delivers information about provenance (first appearance and authors), but in 
time we will add some parameters to receive that information as well.

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?),

Good points. One question we always had: How much time has to pass to consider 
something a “copy” of someone else’s contribution versus that editor's new, own 
contribution (and if it is only  the contribution of “re-discovering” good 
content). I.e.,  if it the original text was absent for 2 years, is the 
re-introduction of good text more productive than just doing a revert of  
vandalism after 1 revision? In the current wikiwho implementation, it’s always 
attributed to the first author right now, like you said.

Also, what about productive deletes? I’m curious if/how you measure those, 
Aaron.


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]).

I strongly agree that more qualitative analysis of the algorithm outputs is 
necessary, as the problem is not that trivial in all cases (as can bee seen 
from our results in [3], where we compared wikiwho with one instantiation of 
A3). I’m also not aware of any other evaluation than the one we did in the 
wikiwho paper. But with Wiki Labels (as far as I understand), we now have a 
great tool to do more human assessment of provenance and content persistence.


Anyhow, great to have some discourse about the topic here :)


Gruß,
Fabian



[1] 
http://f<http://people.aifb.kit.edu/ffl/wikiwho/fp715-floeck.pdf>-squared.org/whovisual<http://squared.org/whovisual>
[2] https://github.com/maribelacosta/wikiwho
[3] http://people.aifb.kit.edu/ffl/wikiwho/fp715-floeck.pdf

--
Fabian Flöck
Research Associate
Computational Social Science department @GESIS
Unter Sachsenhausen 6-8, 50667 Cologne, Germany
Tel: + 49 (0) 221-47694-208
[email protected]<mailto:[email protected]>

www.gesis.org
www.facebook.com/gesis.org

On 22.08.2015, at 17:01, Aaron Halfaker 
<[email protected]<mailto:[email protected]>> wrote:

Luca,

No worries.  Glad to have your code out there.  In a lot of ways, this mailing 
list is a public record, so I wanted to make sure there was a good summary of 
the state to accompany your announcement.  I meant it when I said that I'm glad 
you are working in this space and I look forward to working with you. :)

-Aaron

On Sat, Aug 22, 2015 at 7:26 AM, Luca de Alfaro 
<[email protected]<mailto:[email protected]>> wrote:
Sorry, I meant to say: if there is interest in the code for the Mediawiki 
extension, let me know, and _we_ will clean it up and put on github (you won't 
have to clean it up :-).
Luca

On Sat, Aug 22, 2015 at 7:25 AM, Luca de Alfaro 
<[email protected]<mailto:[email protected]>> wrote:
Thank you Federico.  Done.

BTW, we also had code for a Mediawiki extension that computed this in real 
time.  That code has not yet been cleaned up, but it is available from here: 
https://sites.google.com/a/ucsc.edu/luca/the-wikipedia-authorship-project
If there is interest, I don't think it would be hard to clean up and post 
better to github.
The extension uses the edit hook to attribute the content of every new revision 
of a wiki page, using the "earliest plausible attribution" idea & algo we used 
in the paper.

Luca

On Sat, Aug 22, 2015 at 12:20 AM, Federico Leva (Nemo) 
<[email protected]<mailto:[email protected]>> wrote:
Luca de Alfaro, 22/08/2015 01:51:
So I got inspired, and I cleaned up some code that Michael Shavlovsky
and I had written for this:

https://github.com/lucadealfaro/authorship-tracking

Great! It's always good when code behind a paper is published, it's never too 
late.
If you can please add a link from wikipapers: 
http://wikipapers.referata.com/wiki/Form:Tool

Nemo



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Gruß,
Fabian

--
Fabian Flöck
Research Associate
Computational Social Science department @GESIS
Unter Sachsenhausen 6-8, 50667 Cologne, Germany
Tel: + 49 (0) 221-47694-208
[email protected]<mailto:[email protected]>

www.gesis.org
www.facebook.com/gesis.org






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