The market is pounded with the same hazardous material to users, specifically skin and healthcare. It also affects people both in terms of their health and economy. This makes it necessary to monitor products from user opinions for its protection from duplicates. Online users have increased rapidly and share their opinions on occasions, brands, individuals, products, and events occurring across the world. Millions of users participate in SNSs (Social Networking Sites) like Facebook, Twitters,

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... stagram and WhatsApp etc. Product reviews in public forums like SNSs can provide early clues on such duplicates in terms of allergies or adversities while using them. SA (Sentiment Analysis) can play a significant role in such surveillances. This paper proposes a framework for reviewing experiences in cosmetics in skincare using the Amazon reviews dataset. The proposed technique is based on safety lexicons which are trained for classifications from user sentiments.