Abstract
Web-based social networking can be named as an online stage where individuals can collaborate with each other for their own or expert interests. There is a major issue of Spam in Social Media where Spam is unimportant or spontaneous messages sent over the Internet, commonly to countless, for the reasons for spreading malware, promoting, and phishing and so on. In this paper, YouTube Spam issue is examined as should be obvious that there are various spam remarks on YouTube which do not have any importance to a specific post or video. To examine a gigantic measure of the dataset, a computerized apparatus is required which is administered by Machine Learning where Machine learning is a kind of Artificial Intelligence (AI) that enables programming applications to wind up more exact in anticipating results without being unequivocally customized. The fundamental start of machine learning is to manufacture calculations that can get input information and utilize measurable investigation to anticipate a yield an incentive inside an adequate range. Machine learning calculations are regularly ordered as being supervised or unsupervised. The dataset is examined based on classification technique of supervised learning. In this interest, different popular existing algorithms are compared and another algorithm is produced utilizing ensembling approach. The best precision accomplished is 76.3%.
Keywords
Social Media, YouTube, Artificial Intelligence, Machine Learning, Ensembling Approach
Citations
IRE Journals:
Shikha Kaushik , Prachi Sharma
"Predicting Human Well-Being Using Social Media Via Machine Learning" Iconic Research And Engineering Journals Volume 1 Issue 9 2018 Page 329-334
IEEE:
Shikha Kaushik , Prachi Sharma
"Predicting Human Well-Being Using Social Media Via Machine Learning" Iconic Research And Engineering Journals, 1(9)
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