Abnormal Facebook Multimedia Detection on Facebook using IQR Method - Algur, Siddu P; Jain, Suraj; Bhat, Prashant (International Journal of Computer Sciences and Engineering, 2025)
Recently, discovering outliers among large scale Facebook multimedia have attracted attention of many Facebook mining researchers. There are number of outlier multimedia exists in each category of Facebook multimedia such as- ‘Entertainment’, ‘Sports’, ‘News and Politics’, etc. The task of identifying and manipulate (to remove from the Facebook or to share with others in the Facebook, or to watch/download from the Facebook etc.) such outlier Facebook multimedia have gained significant important research aspect in the area of Facebook Mining Research. In this work, we propose a novel method to detect outliers from the Facebook multimedia based on their metadata objects. Large scale Facebook multimedia metadata objects such as- length, view counts, numbers of comments, rating information are considered for outliers’ detection process. The outlier detection method–Inter-Quartile Range (IQR) is used to find outlier Facebook multimedia of same age. The resultant outliers are analysed and compared as a step in the process of knowledge discovery.