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Information Journal Paper

Title

Predicting the Protest Movements in Cyberspace via Using Data Mining

Pages

  173-197

Abstract

 Background and Aim: Today, various groups in society use Cyberspace to publish Calls for Illegal Gatherings, followed by protests. Therefore, the main purpose of this study is to predict protest flows in Cyberspace based on Data Mining. Method: The present study is applied in terms of purpose and descriptive-analytical in terms of method, in which the information data in documents, organizational documents as well as decentralized databases in police operational categories have been used. The statistical population of the study is all the information data of Illegal Gatherings in Cyberspace that were used for sampling of data processing method and in full. In order to predict and prevent crime, using Rapid Miner software as an open source Data Mining tool in Java, we first identify the main components of illegal aggregation Calls in Cyberspace, the relationships between the components identified in the data, and the data in the data analysis. Results: Among the various implemented models, the decision tree model with 91. 39% accuracy provided the highest result for the data and predicted the occurrence of protest flows, and its most important achievements were designing a model for predicting Illegal Gatherings and determining the effective components in The occurrence of rallies is illegal. Conclusion: The components of "thinking attitude of the publisher of the Calls, the number of visits of the Calls, the subfield of the Calls and the number of members of the sources and targets had the most to the least impact on the occurrence of illegal rallies and protests; In other words, the ideological attitude of the publisher of the Calls has a direct role in creating rallies, and the police can focus on it to predict the possibility of illegal rallies.

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    APA: Copy

    TALEBIAN, HOSEIN. (2021). Predicting the Protest Movements in Cyberspace via Using Data Mining. POLICE MANAGEMENT STUDIES QUARTERLY (PMSQ), 16(3 ), 173-197. SID. https://sid.ir/paper/954602/en

    Vancouver: Copy

    TALEBIAN HOSEIN. Predicting the Protest Movements in Cyberspace via Using Data Mining. POLICE MANAGEMENT STUDIES QUARTERLY (PMSQ)[Internet]. 2021;16(3 ):173-197. Available from: https://sid.ir/paper/954602/en

    IEEE: Copy

    HOSEIN TALEBIAN, “Predicting the Protest Movements in Cyberspace via Using Data Mining,” POLICE MANAGEMENT STUDIES QUARTERLY (PMSQ), vol. 16, no. 3 , pp. 173–197, 2021, [Online]. Available: https://sid.ir/paper/954602/en

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