Wikipedia vandalism detection: combining natural language, metadata, and reputation features

Wikipedia is an online encyclopedia which anyone can edit. While most edits are constructive, about 7% are acts of vandalism. Such behavior is characterized by modifications made in bad faith; introducing spam and other inappropriate content. In this work, we present the results of an effort to integrate three of the leading approaches to Wikipedia vandalism detection: a spatio-temporal analysis of metadata (STiki), a reputation-based system (WikiTrust), and natural language processing features. The performance of the resulting joint system improves the state-of-the-art from all previous methods and establishes a new baseline for Wikipedia vandalism detection. We examine in detail the contribution of the three approaches, both for the task of discovering fresh vandalism, and for the task of locating vandalism in the complete set of Wikipedia revisions.The authors from Universitat Politècnica de València thank also the MICINN research project TEXT-ENTERPRISE 2.0 TIN2009-13391-C04-03 (Plan I+D+i). UPenn contributions were supported in part by ONR MURI N00014-07-1-0907. This research was partially supported by award 1R01GM089820-01A1 from the National Institute Of General Medical Sciences, and by ISSDM, a UCSC-LANL educational collaboration.Adler, BT.; Alfaro, LD.; Mola Velasco, SM.; Rosso, P.; West, AG. (2011). Wikipedia vandalism detection: combining natural language, metadata, and reputation features. En Computational Linguistics and Intelligent Text Processing. 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Análise do movimento do herbicida tebutiuron, por simulação, na cultura da cana-de-açúcar em área de recarga do aquífero Botucatu, Ribeirão Preto/SP.

Com o objetivo de conhecer o comportamento do herbicida Tebutiuron, em área de agricultura intensiva de cana-de-açúcar, localizada na região de Ribeirão Preto, SP, utilizou-se o simulador CMLS-94 - "Chemical Movement in Layered Soils" (Nofziger & Hornsby, 1994). O cenário das simulações foi baseado na data de plantio de cana, 20 de setembro, com aplicação inicial do produto um mês após o plantio, na dose de 1,1 Kg/ha, para um período de simulação de quatro anos. Os resultados mostraram que o Tebutiuron, simulado em solos LR, Transição LR para LE, LE e AQ chega a atingir 30 metros de profundidade no solo AQ, fornecendo indícios de contaminação do lençol freático

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Over the past 30 years, urban policy in Brazil has undergone a major transformation, both in terms of regulatory frameworks and the involvement of citizens in the process of policy-making. As an intense process of institutional innovation and mobilisation for decent publicservices took place, academics started to consider the impact of institutionalisation on the autonomy of social movements. Using empirical evidence from a city in the northeast of Brazil, this article addresses the wider literature on citizen participation and social movements to examine specifically the problem with co-optation. I examine the risks linked to co-optation, risks that can undermine the credibility of social movements as agents of change, and explore the tensions that go beyond the ‘co-optation versus autonomy’ divide, an issue frequently found in the practices of social movements, in their dealings with those in power. In particular, this article explores the learning processes and contentious relationships between mainly institutionally oriented urban movements and local government. This study found that the learning of deliberative skills not only led to changes in the objectives and repertoires of housing movements, but also to the inclusion of new components in their objectives that provide room for creative agency and which, in some cases, might allow them to maintain their autonomy from the state

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Almost every researcher has come through observations that “drift” from the rest of the sample, suggesting some inconsistency. The aim of this paper is to propose a new inconsistent data detection method for continuous geospatial data based in Geostatistics, independently from the generative cause (measuring and execution errors and inherent variability data). The choice of Geostatistics is based in its ideal characteristics, as avoiding systematic errors, for example. The importance of a new inconsistent detection method proposal is in the fact that some existing methods used in geospatial data consider theoretical assumptions hardly attended. Equally, the choice of the data set is related to the importance of the LiDAR technology (Light Detection and Ranging) in the production of Digital Elevation Models (DEM). Thus, with the new methodology it was possible to detect and map discrepant data. Comparing it to a much utilized detections method, BoxPlot, the importance and functionality of the new method was verified, since the BoxPlot did not detect any data classified as discrepant. The proposed method pointed that, in average, 1,2% of the data of possible regionalized inferior outliers and, in average, 1,4% of possible regionalized superior outliers, in relation to the set of data used in the study