Language of Vandalism: Improving Wikipedia Vandalism Detection via Stylometric Analysis

From Wikipedia Quality
Revision as of 06:03, 10 June 2019 by Audrey (talk | contribs) (Overview - Language of Vandalism: Improving Wikipedia Vandalism Detection via Stylometric Analysis)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to: navigation, search

Language of Vandalism: Improving Wikipedia Vandalism Detection via Stylometric Analysis - scientific work related to Wikipedia quality published in 2011, written by Manoj Harpalani, Michael Hart, Sandesh Singh, Rob Johnson and Yejin Choi.

Overview

Community-based knowledge forums, such as Wikipedia, are susceptible to vandalism, i.e., ill-intentioned contributions that are detrimental to the quality of collective intelligence. Most previous work to date relies on shallow lexico-syntactic patterns and metadata to automatically detect vandalism in Wikipedia. In this paper, authors explore more linguistically motivated approaches to vandalism detection. In particular, authors hypothesize that textual vandalism constitutes a unique genre where a group of people share a similar linguistic behavior. Experimental results suggest that (1) statistical models give evidence to unique language styles in vandalism, and that (2) deep syntactic patterns based on probabilistic context free grammars (PCFG) discriminate vandalism more effectively than shallow lexico-syntactic patterns based on n-grams.

Retrieved from "https://wikipediaquality.com/index.php?title=Language_of_Vandalism:_Improving_Wikipedia_Vandalism_Detection_via_Stylometric_Analysis&oldid=17250"