Uncovering Cyberbullying Themes from Unconsented Facebook Pitik Post Through Text Mining Techniques

Pitik, referred as street photography; is a colloquial phrase for taking random photographs, arbitrarily from people without permission and/or consent. Empirically, numerous comments circulating in Facebook Pitik posts containing words related to humiliation, embarrassment, shaming, stalking, and bullying. There are yet no studies conducted confirm or prove the existence extent of cyberbullying themes trends. Cyberbullying not new social media environments technologies trends change over time, medium also changes. We show this study proofs extents cyber bullying posts. In study, we utilized methods natural language processing – specifically text mining emotion polarity computation, known sentiment analysis. Using Facepager software, 68,000 documents/comments collected select pages photographers involved trend posting. Results showed that documents contain 26.29 % pertaining harassment; 35.48% flaming; 19.45% denigration. The negative emotions seen including anger, uncertainty, constraining, fear, sadness, disgust. Findings may help policy makers enhance community standards making its app safer free issues relating cyberbullying, especially unconsented