NDLI: A strategy for automatic moderation of a large data set of users comments

Content Provider	IEEE Xplore Digital Library
Author	Rodrigues Saude, M. de Medeiros Soares, M. Gomes Basoni, H. Ciarelli, P.M. Oliveira, E.
Copyright Year	2014
Description	Author affiliation: Programa de Pos-Grad. em Eng. Eletr. (PPGEE), Univ. Fed. do Espirito Santo (UFES), Vitoria, Brazil (de Medeiros Soares, M.; Ciarelli, P.M.) \|\| Programa de Pos-Grad. em Inf. (PPGI), Univ. Fed. do Espirito Santo (UFES), Vitoria, Brazil (Rodrigues Saude, M.; Gomes Basoni, H.; Oliveira, E.)
Abstract	The increase use of social media and Web 2.0 are daily drawing more people to participate and express their point of views about a variety of subjects. However, there are a huge number of comments which are offensives and sometimes non-politically corrects and so must be hindered from coming up online. This is pushing the services providers to be more careful with the contents they publish to avoid judicial claims. This work proposes the use of automatic classification techniques to identify and only allow to go online harmless comments. We applied various techniques regarding with data processing, such as weighting of terms and the dimensionality reduction. All these techniques have been studied in order to model algorithms to be able to mimic well the human decisions regarding to the comments. The results indicate that we are able to mimic experts decision on 96.78% in the data set used.
Starting Page	1
Ending Page	7
File Size	345333
Page Count	7
File Format	PDF
ISBN	9781479961306
DOI	10.1109/CLEI.2014.6965181
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-09-15
Publisher Place	Uruguay
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Measurement Dimensionality reduction Feature selection Sociology Automatic moderation Vectors Mathematical model Statistics Equations Genetic algorithms
Content Type	Text
Resource Type	Article

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