2017/08/26 by Sebastian Neef, Neef, Sebastian
Computer Science · Social Sciences · #Databases (cs.DB) #Digital Libraries (cs.DL) #Digital Rights Management and Security #Distributed #FOS: Computer and information sciences #Open Source Software Innovations #Parallel #Social and Information Networks (cs.SI) #Software Engineering Research #Wikis in Education and Collaboration #and Cluster Computing (cs.DC) #cs.DB #cs.DC #cs.DL #cs.SI
paper · pdf · doi:10.48550/arxiv.1709.01142
arxiv created 2017/08/26 · openalex publication_date 2017/08/26 · arxiv updated 2017/09/06 · openalex created_date 2022/09/03 · openalex updated_date 2026/07/28
Wikipedia, an open collaborative website, can be edited by anyone, even anonymously, thus becoming victim to ill-intentioned changes. Therefore, ranking Wikipedia authors by calculating impact measures based on the edit history can help to identify reputational users or harmful activity such as vandalism \citeAdler:2008:MAC:1822258.1822279. However, processing millions of edits on one system can take a long time. The author implements an open source framework to calculate such rankings in a distributed way (MapReduce) and evaluates its performance on various sized datasets. A reimplementation of the contribution measures by \citeauthorAdler:2008:MAC:1822258.1822279 demonstrates its extensibility and usability, as well as problems of handling huge datasets and their possible resolutions. The results put different performance optimizations into perspective and show that horizontal scaling can decrease the total processing time.