Analysis of Cyberbullying Incidence among Filipina Victims: A Pattern Recognition using Association Rule Extraction

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Frederick F. Patacsil 1,*

1. College of Computing, Pangasinan State University-Urdaneta City Campus, Philippines

* Corresponding author.


Received: 1 Feb. 2019 / Revised: 10 Jun. 2019 / Accepted: 14 Aug. 2019 / Published: 8 Nov. 2019

Index Terms

Cyberbullying, association rule, pattern recognition, associative approach


Cyberbullying is an intentional action of harassment along the complex domain of social media utilizing information technology online. This research experimented unsupervised associative approach on text mining technique to automatically find cyberbullying words, patterns and extract association rules from a collection of tweets based on the domain / frequent words. Furthermore, this research identifies the relationship between cyberbullying keywords with other cyberbullying words, thus generating knowledge discovery of different cyberbullying word patterns from unstructured tweets. The study revealed that the type of dominant frequent cyberbullying words are intelligence, personality, and insulting words that describe the behavior, appearance of the female victims and sex related words that humiliate female victims. The results of the study suggest that we can utilize unsupervised associative approached in text mining to extract important information from unstructured text. Further, applying association rules can be helpful in recognizing the relationship and meaning between keywords with other words, therefore generating knowledge discovery of different datasets from unstructured text.

Cite This Paper

Frederick F. Patacsil, "Analysis of Cyberbullying Incidence among Filipina Victims: A Pattern Recognition using Association Rule Extraction", International Journal of Intelligent Systems and Applications(IJISA), Vol.11, No.11, pp.48-57, 2019. DOI:10.5815/ijisa.2019.11.05


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