Identification of Dominant Topics in Child-Related Hashtags on Social Media X Using Word Cloud

Abstract

This study aims to identify dominant topics within child-related content (Konten Anak) hashtags on social media platform X. The dataset comprises 1,967 tweets collected through a crawling process using relevant keywords and hashtags. The analysis was conducted using an exploratory approach with Word Cloud visualization to display the most frequently occurring words in the tweets. The analytical process included pre-processing steps such as transformation, tokenization, and filtering to enhance visualization accuracy. The results indicate that the words 'children' and 'content' dominate the discussion; however, several concerning terms such as 'fantasy', 'incest', and 'pornography' were also identified, suggesting potential abuse or exploitation of child-related content on social media.