Zobrazeno 1 - 10
of 48
pro vyhledávání: '"Flöck, Fabian"'
As NLP models are increasingly deployed in socially situated settings such as online abusive content detection, it is crucial to ensure that these models are robust. One way of improving model robustness is to generate counterfactually augmented data
Externí odkaz:
http://arxiv.org/abs/2109.07022
'I Updated the
': The Evolution of References in the English Wikipedia and the Implications for Altmetrics
With this work, we present a publicly available dataset of the history of all the references (more than 55 million) ever used in the English Wikipedia until June 2019. We have applied a new method for identifying and monitoring references in Wikipedi
Externí odkaz:
http://arxiv.org/abs/2010.03083
Publikováno v:
Proceedings of the 15th International AAAI Conference on Web and Social Media (ICWSM), 2021
Research has focused on automated methods to effectively detect sexism online. Although overt sexism seems easy to spot, its subtle forms and manifold expressions are not. In this paper, we outline the different dimensions of sexism by grounding them
Externí odkaz:
http://arxiv.org/abs/2004.12764
Peoples' activities and opinions recorded as digital traces online, especially on social media and other web-based platforms, offer increasingly informative pictures of the public. They promise to allow inferences about populations beyond the users o
Externí odkaz:
http://arxiv.org/abs/1907.08228
Autor:
Wang, Zijian, Hale, Scott A., Adelani, David, Grabowicz, Przemyslaw A., Hartmann, Timo, Flöck, Fabian, Jurgens, David
Publikováno v:
Proceedings of the 2019 World Wide Web Conference (WWW '19), May 13--17, 2019, San Francisco, CA, USA
Social media provide access to behavioural data at an unprecedented scale and granularity. However, using these data to understand phenomena in a broader population is difficult due to their non-representativeness and the bias of statistical inferenc
Externí odkaz:
http://arxiv.org/abs/1905.05961
Autor:
Posch, Lisa, Bleier, Arnim, Flöck, Fabian, Lechner, Clemens M., Kinder-Kurlanda, Katharina, Helic, Denis, Strohmaier, Markus
Publikováno v:
Human Computation, 9(1), 22-57 (2022)
Since its emergence roughly a decade ago, microtask crowdsourcing has been attracting a heterogeneous set of workers from all over the globe. This paper sets out to explore the characteristics of the international crowd workforce and offers a cross-n
Externí odkaz:
http://arxiv.org/abs/1812.05948
As one of the richest sources of encyclopedic information on the Web, Wikipedia generates an enormous amount of traffic. In this paper, we study large-scale article access data of the English Wikipedia in order to compare articles with respect to the
Externí odkaz:
http://arxiv.org/abs/1805.04022
Crowd employment is a new form of short term employment that has been rapidly becoming a source of income for a vast number of people around the globe. It differs considerably from more traditional forms of work, yet similar ethical and optimization
Externí odkaz:
http://arxiv.org/abs/1711.03115
Previous research has shown the existence of gender biases in the depiction of professions and occupations in search engine results. Such an unbalanced presentation might just as likely occur on Wikipedia, one of the most popular knowledge resources
Externí odkaz:
http://arxiv.org/abs/1706.03848
We present a dataset that contains every instance of all tokens (~ words) ever written in undeleted, non-redirect English Wikipedia articles until October 2016, in total 13,545,349,787 instances. Each token is annotated with (i) the article revision
Externí odkaz:
http://arxiv.org/abs/1703.08244