Abstract
Nowadays, a new area of marketing and communication has emerged thanks to internet reviews, bridging the gap between conventional word-of-mouth and a viral feedback loop that can sway consumers' perceptions. Reviews of specific medications, however, are much more important in the medical industry because they may be used to track side effects and determine how consumers feel about a medication overall. This paper's main goal is to use medication reviews to categorize patient conditions, specifically Type 2 Diabetes, High Blood Pressure, and Depression. The goal is to study and understand the effectiveness of drugs for specific conditions and their potential side effects by analysing patient reviews, ratings, and useful counts. The insights gained from this analysis can be used to recommend suitable drugs for patients based on their condition and the experiences of other patients with similar conditions. Key Words: TF-IDF, BOW, Passive Aggressive Classifier, stop word.
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