Conducted by PIT
, Started on 2019 -
Completed on 2020
Completed
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Cybercrime is defined as criminal activities conducted in cyberspace by means of Internet technology which affects every government, business, and individual. However, many studies reveal different viewpoints towards this phenomenon. This study covers the glut of opinions from the top five countries with the highest published articles related to Cyber Crime-based on Google trends. The data gathered from online articles were processed using the Web Mining procedure such as Unsupervised Machine Learning with the utilization of Latent Dircihlet Allocation (LDA) algorithm applied for content examination of the document gathered. Five underlying themes extrcated by the researchers in light of the outcomes created by the R-Programming application upheld the writing, literature, and analysis of data. Results reveal that the highest probability of topics were discussing the international cyber-attacks on government services. However, this paper was limited only on the availability of articles relative to cybercrimes, and it is suggested that further research study be conducted in order to assess the reliability of the model being used.