STiki: An anti-vandalism tool for wikipedia using spatio-temporal analysis of revision metadata
|STiki: An anti-vandalism tool for wikipedia using spatio-temporal analysis of revision metadata|
|Author(s)||West A.G., Kannan S., Lee I.|
|Published in||Proceedings of WikiSym 2010 - The 6th International Symposium on Wikis and Open Collaboration|
|Keyword(s)||Unknown (Extra: End-users, Language independents, Natural language processing, Open-source code, Server-side processing, Spatio-temporal properties, Spatiotemporal analysis, Wikipedia, Computational linguistics, Light polarization, Natural language processing systems, Metadata)|
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STiki: An anti-vandalism tool for wikipedia using spatio-temporal analysis of revision metadata is a 2010 conference paper written in English by West A.G., Kannan S., Lee I. and published in Proceedings of WikiSym 2010 - The 6th International Symposium on Wikis and Open Collaboration.
STiki is an anti-vandalism tool for Wikipedia. Unlike similar tools, STiki does not rely on natural language processing (NLP) over the article or diff text to locate vandalism. Instead, STiki leverages spatio-temporal properties of revision metadata. The feasibility of utilizing such properties was demonstrated in our prior work, which found they perform comparably to NLP-efforts while being more efficient, robust to evasion, and language independent. STiki is a real-time, on-Wikipedia implementation based on these properties. It consists of, (1) a server-side processing engine that examines revisions, scoring the likelihood each is vandalism, and, (2) a client-side GUI that presents likely vandalism to end-users for definitive classification (and if necessary, reversion on Wikipedia). Our demonstration will provide an introduction to spatio-temporal properties, demonstrate the STiki software, and discuss alternative research uses for the open-source code.
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