• Informatization Policy
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• v.26 no.4
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• pp.85-106
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• 2019

Recently, there have been increasing cases of collective petitions filed in the electronic petitions system. However, there is no efficient management system, raising concerns on side effects such as increased administrative workload and mass production of social conflicts. Aimed at suggesting a methodology for estimating electronic collective petitions using anomaly detection and corpus linguistics-based content analysis, this study conducted the followings: i) a theoretical review of the concept of collective petitions, ii) estimation of electronic collective petitions using anomaly detection based on nonparametric unsupervised learning, iii) a content similarity analysis on petitions using n-gram cosine angle distance, and iv) a case study on the Voice of Citizens of Changwon City, through which the utility of the proposed methodology, policy implications and future tasks were reviewed.