@@ -184,23 +184,35 @@ This presents (syn!) an excellent starting point for analysis of the edit filter
However, valuable lessons can be learnt (about the communities, models of governance, usefulness of filters, etc.) from comparing edit filter use across different language versions.
Just recall, how for instance the role of edit filter managers doesn't exist in certain language versions (comapare chapter~\ref{}) and instead it is administrators who have an \emph{abusefilter-modify} permission next to their other rights.
Secondly, unfortunately, including an ethnographic analysis was not possible.
Secondly, unfortunately, conducting a classical ethnographic analysis was not possible.
It would have been particularly insightful to talk to edit filter managers (above all such who are simultaneously also bot operators) and developers of the extension, as well as regular editors who have tripped a filter.
This is partially due to the fact that we employ a computer science perspective on the question and partially due to limited time.
I really only used ``found data'' (compare~\ref{sec:trace-ethnography}) (well I also attempted to interpret the found data and link it) and future studies can and should use the first insights of the current research as interview prompts
Thirdly, the manual filter classification was undertaken by one person only, so biases of this person have certainly shaped the labels.
Thirdly, the manual filter classification was undertaken by one person only (me), so biases of this person have certainly shaped the labels.
Fourth, edit filter history table was not available, so no hollistic quantitative analysis of the filters' development over time was possible.
Fifth, no access to the details of hidden filters, so no insights into the areas they target (although couple of educated guesses: bunch of persistent long term vandal, who often employ sockpuppets; harassment/personal attack cases hidden to protect the affected persons)
%TODO describe also negative results!
%Data
Following other pages looked interesting or related, but were left out, mainly because of insufficient time.
(Is there a better reasoning why I looked at the pages I looked at specifically, while left particularly these other pages for later?)
I really only used ``found data'' (compare~\ref{sec:trace-ethnography}) (well I also attempted to interpret the found data and link it) and future studies can and should use the first insights of the current research as interview prompts
%TODO Discuss ethical concerns of thickening traces and its clash with open science aspiration here?
%********************
% Filters vs bots
% Investigation of edit filter managers who are also bot operators: what do they implement when?
\begin{comment}
Question:
Oftentimes edit filter managers are also bot operators; how would they decide when to implement a filter and when a bot?
%TODO: ask people! (on IRC?)
I've compiled a list of edit filter managers who are simultaneously also bot operators;
I've further assembled the bots they run and made notes on the bots that seem to be relevant to vandalism prevention/quality assurance
I'm currently trying to determine from document traces what filter contributions the corresponding edit filter managers had and whether they are working on filters similar to the bots they operate.
Insight is currently minimal, since abuse\_filter\_history table is not available and we can only determine what filters an edit filter manager has worked on from limited traces such as: last modifier of the filter from abuse\_filter table; editors who signed their comments from abuse\_filter table; probably some noticeboards or talk page archives, but I haven't looked into these so far.
@@ -16,6 +16,7 @@ The present thesis just lay the ground work for future edit filters research.
I gave an initial overview and summarised/showed/pointed out interesting paths/framework for future research (syn!).
% TODO Refer back to title! Who is allowed to publish? Who decides?
% Refer to the rumour about gendering filter on German Wikipedia
Special attention: following edit filters from DE Wikipedia:
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@@ -50,8 +51,6 @@ Criticism: threaten free speech, freedom of press and creativity
edit filters implemented an infrastructure that enables censorship
%TODO check literature! is there something that can be used as argument why rule based system are in use?
The planned introduction of upload filters by the EU copyright reform is seen critically by Wikimedia Germany:
\begin{figure}
\centering
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@@ -107,17 +106,3 @@ tribute to a band by playing live along with the commercial recording as a backi
and oblivious to nuance, encourages these kinds of shotgun tactics." //compare blog post on upload filters
\end{comment}
%********************
% Filters vs bots
% Investigation of edit filter managers who are also bot operators: what do they implement when?
\begin{comment}
Question:
Oftentimes edit filter managers are also bot operators; how would they decide when to implement a filter and when a bot?
%TODO: ask people! (on IRC?)
I've compiled a list of edit filter managers who are simultaneously also bot operators;
I've further assembled the bots they run and made notes on the bots that seem to be relevant to vandalism prevention/quality assurance
I'm currently trying to determine from document traces what filter contributions the corresponding edit filter managers had and whether they are working on filters similar to the bots they operate.
Insight is currently minimal, since abuse\_filter\_history table is not available and we can only determine what filters an edit filter manager has worked on from limited traces such as: last modifier of the filter from abuse\_filter table; editors who signed their comments from abuse\_filter table; probably some noticeboards or talk page archives, but I haven't looked into these so far.
