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.

翻译：从定义上讲，人们对禁忌话题往往讳莫如深甚至不愿谈论。由于性、健康与暴力等话题在多数文化中均属禁忌，导致这些领域的重要信息难以获取。以维基百科为代表的同行生产知识库，能否成为向公众提供禁忌话题信息的有效途径？考虑到依赖同样可能回避禁忌话题的志愿者，这种同行生产模式能否产出高质量的禁忌话题信息？本研究旨在探索禁忌在志愿者生产知识库中的作用机制。我们通过开发新型计算方法识别禁忌话题，并运用该方法筛选出英文维基百科中一组禁忌相关条目。研究发现：禁忌类文章较非禁忌类文章更受欢迎，且更易遭受恶意破坏。尽管频繁遭到破坏，禁忌类文章的质量仍高于非禁忌类文章。我们假设社会污名化态度会促使禁忌话题贡献者降低身份可识别性。虽然部分研究结果支持该假设，但令人意外的是，贡献者在其他方面反而增强了自身的可识别性。