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  1. By definition, people are reticent or even unwilling to talk about taboo subjects. Because subjects like sexuality, health, and violence are taboo in most cultures, important information on each of these subjects can be difficult to obtain. Are peer produced knowledge bases like Wikipedia a promising approach for providing people with information on taboo subjects? With its reliance on volunteers who might also be averse to taboo, can the peer production model produce high-quality information on taboo subjects? In this paper, we seek to understand the role of taboo in knowledge bases produced by volunteers. We do so by developing a novel computational approach to identify taboo subjects and by using this method to identify a set of articles on taboo subjects in English Wikipedia. We find that articles on taboo subjects are more popular than non-taboo articles and that they are frequently vandalized. Despite frequent vandalism attacks, we also find that taboo articles are higher quality than non-taboo articles. We hypothesize that stigmatizing societal attitudes will lead contributors to taboo subjects to seek to be less identifiable. Although our results are consistent with this proposal in several ways, we surprisingly find that contributors make themselves more identifiable in others. 
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    Free, publicly-accessible full text available September 28, 2024
  2. Many online communities rely on postpublication moderation where contributors-even those that are perceived as being risky-are allowed to publish material immediately and where moderation takes place after the fact. An alternative arrangement involves moderating content before publication. A range of communities have argued against prepublication moderation by suggesting that it makes contributing less enjoyable for new members and that it will distract established community members with extra moderation work. We present an empirical analysis of the effects of a prepublication moderation system called FlaggedRevs that was deployed by several Wikipedia language editions. We used panel data from 17 large Wikipedia editions to test a series of hypotheses related to the effect of the system on activity levels and contribution quality. We found that the system was very effective at keeping low-quality contributions from ever becoming visible. Although there is some evidence that the system discouraged participation among users without accounts, our analysis suggests that the system's effects on contribution volume and quality were moderate at most. Our findings imply that concerns regarding the major negative effects of prepublication moderation systems on contribution quality and project productivity may be overstated.

     
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  3. What factors influence the decision to vandalize? Although the harm is clear, the benefit to the vandal is less clear. In many cases, the thing being damaged may itself be something the vandal uses or enjoys. Vandalism holds communicative value: perhaps to the van- dal themselves, to some audience at whom the vandalism is aimed, and to the general public. Viewing vandals as rational community participants despite their antinormative behavior offers the possibility of engaging with or countering their choices in novel ways. Rational choice theory (RCT) as applied in value expectancy theory (VET) offers a strategy for characterizing behaviors in a framework of rational choices, and begins with the supposition that subject to some weighting of personal preferences and constraints, individuals maximize their own utility by committing acts of vandalism. This study applies the framework of RCT and VET to gain insight into vandals’ preferences and constraints. Using a mixed-methods analysis of Wikipedia, I combine social computing and criminological perspectives on vandalism to propose an ontology of vandalism for online content communities. I use this ontology to categorize 141 instances of vandalism and find that the character of vandalistic acts varies by vandals’ relative identifiability, policy history with Wikipedia, and the effort required to vandalize. 
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  4. User-generated content sites routinely block contributions from users of privacy-enhancing proxies like Tor because of a perception that proxies are a source of vandalism, spam, and abuse. Although these blocks might be effective, collateral damage in the form of unrealized valuable contributions from anonymity seekers is invisible. One of the largest and most important user-generated content sites, Wikipedia, has attempted to block contributions from Tor users since as early as 2005. We demonstrate that these blocks have been imperfect and that thousands of attempts to edit on Wikipedia through Tor have been successful. We draw upon several data sources and analytical techniques to measure and describe the history of Tor editing on Wikipedia over time and to compare contributions from Tor users to those from other groups of Wikipedia users. Our analysis suggests that although Tor users who slip through Wikipedia's ban contribute content that is more likely to be reverted and to revert others, their contributions are otherwise similar in quality to those from other unregistered participants and to the initial contributions of registered users. 
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  5. User-generated content sites routinely block contributions from users of privacy-enhancing proxies like Tor because of a perception that proxies are a source of vandalism, spam, and abuse. Although these blocks might be effective, collateral damage in the form of unrealized valuable contributions from anonymity seekers is invisible. One of the largest and most important user-generated content sites, Wikipedia, has attempted to block contributions from Tor users since as early as 2005. We demonstrate that these blocks have been imperfect and that thousands of attempts to edit on Wikipedia through Tor have been successful. We draw upon several data sources and analytical techniques to measure and describe the history of Tor editing on Wikipedia over time and to compare contributions from Tor users to those from other groups of Wikipedia users. Our analysis suggests that although Tor users who slip through Wikipedia's ban contribute content that is more likely to be reverted and to revert others, their contributions are otherwise similar in quality to those from other unregistered participants and to the initial contributions of registered users. 
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