Izvorni znanstveni članak
https://doi.org/10.24138/jcomss-2021-0139
Identifying Causal Structures from Cyberstalking: Behaviors Severity and Association
Shkurte Luma-Osmani
; Faculty of Contemporary Sciences and Technologies, South East European University, Tetovo, North Macedonia and Faculty of Natural Sciences and Mathematics, University of Tetova, Tetovo, Republic of North Macedonia
Florije Ismaili
; Faculty of Contemporary Sciences and Technologies, South East European University, Tetovo, North Macedonia
Pankaj Pathak
; Symbiosis Institute of Digital and Telecom Management, Symbiosis International (Deemed University), Pune, India
Xhemal Zenuni
; Faculty of Contemporary Sciences and Technologies, South East European University, Tetovo, North Macedonia
Sažetak
This paper presents an etiological cyberstalking study, meaning the use of various technologies and internet in general to harass or to stalk someone. The novelty of the paper is the multivariate empirical approach of cyberstalking victimization that has received less attention from the research community. Also, there is a lack of such studies from the causal perspective. It happens, since in most of the studies, a priority is given on a single causation identification, whereas the data examination used for mining causal relationships in this paper presents a novel and great potential to detect combined or multiple cause factors. The paper focuses in the impact that variables such as age, gender and the fact whether the participant has ever harassed someone, is related to the fact of being victim of cyberstalking. The research aims to find the causes of cyberstalking in high school’s teenagers. Furthermore, an exploratory data analysis has been performed. A weak and moderate correlation between the factors on the dataset is emphasized. The odds ratio among the variables has been calculated, which implies that girls are twice as likely as boys to be cyberstalked. Similarly, concerning outcomes related to cyberstalking frequency recidivism are noticed.
Ključne riječi
causality; causal rules; cyberstalking; Data Mining
Hrčak ID:
270750
URI
Datum izdavanja:
31.3.2022.
Posjeta: 1.196 *