Wikipedia

By Sylvain Firer-Blaess, Christian Fuchs. 2014

The task of this article is to analyze the political economy of Wikipedia. We discuss the specifics of Wikipedia’s mode of production. The basic principles of what we call the info-communist mode of production will be presented. Our analysis is grounded in Marxist philosophy and Marxist political economy, and is connected to the current discourse about the renewal and reloading of the idea of communism that is undertaken by thinkers like Slavoj Žižek and Alain Badiou. We explore to which extent Wikipedia encompasses principles that go beyond the capitalist mode of production and represent the info-communist mode of production. We present the subjective dimension of the mode of production (cooperative labor), the objective dimension of the mode of production (common ownership of the means of production), and the subject–object dimension of the mode of production (the effects and products of the mode of production).

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Citations in the corpus

Conscientious Classification: A Data Scientist's Guide to Discrimination-Aware Classification (2017, neutral): “This is known as the Cross Industry Standard Process for Data Mining (CRISP-DM), 18 and it has been a standard for well more than a decade.”
Discovering Diverse Multi-Agent Strategic Behavior via Reward Randomization (2021, background): “Each player starts with one cell but can split a sufﬁciently large cell into two, allowing them to control multiple cells (Wikipedia, 2020).”
Disinformation on the Web: Impact, Characteristics, and Detection of Wikipedia Hoaxes (2016, background): “The Wikipedia community guidelines deﬁne a hoax as “an attempt to trick an audience into believing that something false is real”, and therefore consider it “simply a more obscure, less obvious form of vandalism” [39].”
Sharing and Web 2.0: The emergence of a keyword (2013, background): “…metrics, for visits to websites in its social network category for July 2011; data compiled in Wikipedia on the size of the membership of the largest SNSs (Wikipedia, 2011); and the section on the history of SNSs in boyd and Ellison’s survey of the field (2008: see especially Figure 1 on p. 212).”
Measuring the Size of Large No-Limit Poker Games (2013, background): “This number allows us to compare a game against other games such as chess or backgammon, which have 10 47 and 10 20 distinct game states respectively (not including transpositions)[10].”
A feature selection model based on genetic rank aggregation for text sentiment classification (2017, background): “It is an interdisciplinary research field that combines tools and techniques from natural language processing, text mining and computational linguistics [1].”
A Survey on Malware Detection Using Data Mining Techniques (2017, background): “Scareware : Scareware is a recent type of malicious ﬁle that is designed to trick a user into buying and downloading unnecessary and potentially dangerous software, such as fake antivirus protection [Wikipedia 2016], which has posed severe ﬁnancial and privacy-related threats to the victims.”
Pattern of early human-to-human transmission of Wuhan 2019-nCoV (2020, background): “The outbreak apparently started from a single or multiple zoonotic transmission events at a wet market in Wuhan, and has since resulted in 655 conﬁrmed cases in China and several other countries by January 23, 2020 [3].”
Adversarial Attack and Defense on Graph Data: A Survey (2018, background): “It can be used to evaluate the performance of recommender system as well [44]. nDCG@K [135] is another metric to evaluate the robustness of recommendation models [95].”
Two-Player Games for Efficient Non-Convex Constrained Optimization (2018, background): “For example, the “80% rule” of Equation 2 can be found in the HOPA Act of 1995 [Wikipedia, 2018], and it requires an 80% threshold in terms of the number of positive predictions —not a relaxation—which is precisely the target that the proxy-Lagrangian approach will attempt to hit.”
MnnFast: A Fast and Scalable System Architecture for Memory-Augmented Neural Networks (2019, methodology): “For example, when MemNN uses Wikipedia for training, the number of story sentences is around 200M [79].”