Ensuring the Integrity of Wikipedia: A Data Science Approach
Authors | Francesca Spezzano |
|---|---|
Publication date | 2017 |
ISSN | 16130073 |
Links | Original |
Ensuring the Integrity of Wikipedia: A Data Science Approach - scientific work about Wikipedia quality published in 2017, written by Francesca Spezzano.
Overview
In this paper, authors present their research on the problem of ensuring the integrity of Wikipedia, the world’s biggest free encyclopedia. As anyone can edit Wikipedia, many malicious users take advantage of this situation to make edits that compromise pages’ content quality. Specifically, authors present DePP, the state-of-the-art tool that detects article pages to protect with an accuracy of 93% and authors introduce their research on identifying spam users. Authors show that authors are able to classify spammers from benign users with 80.8% of accuracy and 0.88 mean average precision.
Embed
Wikipedia Quality
Spezzano, Francesca. (2017). "[[Ensuring the Integrity of Wikipedia: A Data Science Approach]]". CEUR Workshop Proceedings Volume 2037, 2017. ISSN: 16130073.
English Wikipedia
{{cite journal |last1=Spezzano |first1=Francesca |title=Ensuring the Integrity of Wikipedia: A Data Science Approach |date=2017 |issn=16130073 |url=https://wikipediaquality.com/wiki/Ensuring_the_Integrity_of_Wikipedia:_A_Data_Science_Approach |journal=CEUR Workshop Proceedings Volume 2037, 2017}}
HTML
Spezzano, Francesca. (2017). "<a href="https://wikipediaquality.com/wiki/Ensuring_the_Integrity_of_Wikipedia:_A_Data_Science_Approach">Ensuring the Integrity of Wikipedia: A Data Science Approach</a>". CEUR Workshop Proceedings Volume 2037, 2017. ISSN: 16130073.
