Slash(dot) and burn: distributed moderation in a large online conversation space
By Cliff Lampe, Paul Resnick. 2004
461 citations recorded by the source corpus.
Subfields: Information Systems
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Information Systems
- John Riedl
- J. Konstan
- Loreen Terveen
- Michael S. Bernstein
- Jure Leskovec
- Kristina Lerman
- Shyong K. Lam
- Gediminas Adomavicius
Citations in the corpus
- Leveraging Position Bias to Improve Peer Recommendation (2014, background): “peer recommendation are biased [4,5] and inconsistent, with the”
- Self-Governance Through Group Discussion in Wikipedia (2011, background): “Topic-specific forums like FatSecret (Black, Bute, & Russell, 2010) and more general sites like Reddit or Slashdot also generate community through participant-managed interaction (Lampe & Resnick, 2004).”
- Algorithmic content moderation: Technical and political challenges in the automation of platform governance (2020, background): “…administrators who formed part of the community, platform companies operate at a scale that has led them away from traditional practices of community moderation (Lampe and Resnick, 2004) and towards what has been termed ‘commercial content moderation’ or ‘platform moder-ation’ (Roberts, 2018).”
- Cooperation and quality in wikipedia (2007, result): “Other characteristics such asfactual accuracy [13, 12, 10], credibility [6], revert times [31], and formality of language [11] have been used to assess small samples of Wikipedia s articles and in some cases compare them to articles of traditional encyclopedias.”
- Anyone Can Become a Troll: Causes of Trolling Behavior in Online Discussions (2017, background): “Methods of combating such behavior include comment ranking [39], moderation [53, 67], early troll identification [14, 18], and interface redesigns that encourage civility [51, 52].”
- Bots, bespoke, code and the materiality of software platforms (2014, background): “As an example, Lessig references the way many discussion-oriented websites have implemented ‘democracy like’ (285) software systems, like Slashdot's distributed moderation and meta-moderation features (Lampe & Resnick, 2004; Poor, 2005).”
- Eliciting Informative Feedback: The Peer-Prediction Method (2005, background): “The literature discusses a number of strictly proper scoring rules.”
- Predicting the popularity of online content (2008, background): “Activity fluctuations, user commenting behavior prediction, the ensuing social network, and community moderation structure is the focus of studies on Slashdot [15, 12, 17 ], a portal that is similar in spirit to Digg.”
- Online Harassment and Content Moderation (2018, background): “ese mechanisms include using a small number of human moderators who manually remove abusive posts [25], moderating through a voting mechanism where registered users up-vote or down-vote each submission [27], and allowing users to ag abusive content [11].”
- Lurking? cyclopaths?: a quantitative lifecycle analysis of user behavior in a geowiki (2010, background): “For example, Whit-taker et al. [31] and Jones et al. [14] revealed the dynamics of large scale discussions; Lampe and Resnick investigated the effectiveness of distributed moderation for information filtering [16].”
- 4chan and /b/: An Analysis of Anonymity and Ephemerality in a Large Online Community (2011, background): “Some scholars have questioned these design approaches, suggesting that anonymous contributions and ephemeral participation online can be desirable (Lampe and Resnick 2004; Copyright c 2011, Association for the Advancement of Artificial Intelligence (www.aaai.org).”
- Shepherding the crowd yields better work (2012, background): “Likewise, online communities often provide infrastructure for moderators to review others’ content and to encourage the growth of newer members [6,20].”
- Normative influences on thoughtful online participation (2011, background): “While such regulation has traditionally been achieved through moderation systems [18], recent research has also focused on subjective perceptions that people form about their online social situations.”
- Towards quality discourse in online news comments (2011, background): “Such systems work by aggregating community members’ moderation judgments in order to indicate the quality of comments [ 18 , 23].”