Participation anticipating in elections using data mining methods

Anticipating the political behavior of people will be considerable help for election candidates to assess the possibility of their success and to be acknowledged about the public motivations to select them. In this paper, we provide a general schematic of the architecture of participation anticipati...

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Bibliographic Details
Published in:arXiv.org 2013-07
Main Authors: Amin Babazadeh Sangar, Khaze, Seyyed Reza, Ebrahimi, Laya
Format: Article
Language:English
Subjects:
Algorithms
Bayesian analysis
Classification
Data mining
Elections
Human behavior
Presidential elections
Online Access:Get full text
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Summary:Anticipating the political behavior of people will be considerable help for election candidates to assess the possibility of their success and to be acknowledged about the public motivations to select them. In this paper, we provide a general schematic of the architecture of participation anticipating system in presidential election by using KNN, Classification Tree and Na\"ive Bayes and tools orange based on crisp which had hopeful output. To test and assess the proposed model, we begin to use the case study by selecting 100 qualified persons who attend in 11th presidential election of Islamic republic of Iran and anticipate their participation in Kohkiloye & Boyerahmad. We indicate that KNN can perform anticipation and classification processes with high accuracy in compared with two other algorithms to anticipate participation.
ISSN:2331-8422