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luvaseva
wikifilters
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23a7aa5d
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23a7aa5d
authored
5 years ago
by
Lyudmila Vaseva
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@@ -1671,11 +1671,50 @@ community's goals changed during the period of exponential growth
automated quality control systems and are overwhelmed by the complexity of the rule system."
contributions of the paper:
1)
First,
we implicate Wikipedia’s primary quality control mechanism (Stvilia, 2005), the rejection of
"
1) we implicate Wikipedia’s primary quality control mechanism (Stvilia, 2005), the rejection of
unwanted contributions, as a strong, negative predictor of the retention of high quality
newcomers and show that these newcomers’ contributions are being rejected at an increasing
rate. Next, we show how algorithmic tools, which were built to make the work of controlling the
rate
2) we show how algorithmic tools, which were built to make the work of controlling the
quality of Wikipedia’s content more efficient, exacerbate the effect of rejection on desirable
newcomer retention and circumvent Wikipedia’s conflict resolution process.
Finally, we show
how calcification has made Wikipedia’s policy environment less adaptable and increased the
newcomer retention and circumvent Wikipedia’s conflict resolution process.
3) we show
how calcification has made Wikipedia’s policy environment less adaptable and increased the
difficulty of contributing to community rules – especially for newcomers."
"Wikipedia’s open contribution system constitutes an informal
peer review where all contributions are initially accepted;"
"the definition of “unwanted” contribution has certainly
changed over time. While presenting at Wikimania in 2006, Jimmy Wales urged Wikipedians to
change their focus from quantity to quality."
"shift from Wikipedia as
a catch-all for encyclopedia-like content to a more restrictive project."
"external pressures for Wikipedia to tighten its review process. After high profile
cases of libel"
"the length of the article at the time of contribution was a significant predictor of
rejection."
"Hypothesis: Rejection & retention. Increasing rates of rejection have caused a decrease in
the retention of desirable newcomers."
"Hypothesis: Tool use & consequences. The use of algorithmic tools to reject newcomer
contributions is exacerbating the decrease in desirable newcomer retention."
"In 2006, Wikipedia administrator Tawker initiated a new
genre: the vandal fighter bot." //TODO: Would be interesting for timeline; however I cant find which bot it was
"using a simple text pattern matcher."
"After years of iteration, vandal fighter bots are in wide use
in mid-2012. ClueBot NG uses machine learning and neural network approaches to identify and
reject over 40,000 acts of vandalism a month, with a median time to revert of five seconds."
//TODO median time can be used in the funnel diagram
"Human-computation tools [..] catch the damage the bots miss"
"re-introduce human judgment into the vandal fighting task."
"These algorithmic tools have apparently made quality control both more efficient and more
effective. Previous work has shown that the duration during which vandalism is visible in an
article has been decreasing (Kittur, 2007; Priedhorsky, 2007). These tools also reduce the
amount of volunteer effort that must be devoted to rejecting unwanted contributions"
//argument in favour of not only a difference of scale, but also of substance
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