SENTIMENT ANALYSIS OF RESTAURANT REVIEWS USING AI

Abstract - As online reviews become a critical consumer decision point, sentiment analysis has become a significant area of research. This paper investigates Artificial Intelligence (AI) and Google's Gemini in restaurant review analysis, customer sentiment determination, and business strategy improvement.

The utilization of artificial intelligence has changed the landscape of how businesses engage with customer reviews and what they can learn from the reviews. AI algorithms can analyze huge amounts of review content in bulk, determining patterns that can develop insights that can be acted upon in a flexible way. Google has created Gemini, an advanced AI model that improves upon this process with improvements in the understanding of language, context, and even sentiment (or intent). When a restaurant incorporates Gemini into their review data analysis, they can better understand customers emotions, preferences, and problems to make better decisions and adjust levels of service even better.

We explain the ability of Gemini, along with AI overall, to categorize and analyze sentiments from textual information, in order to determine whether reviews have been categorized as positive (expressing satisfaction), negative (expressing dissatisfaction), or neutral. In addition, AI also has the capability of providing suggestions for satisfying and dissatisfying experiences based on the content of sentiments. The study also considers how real-time AI-powered sentiment analysis can support companies in being more agile in their responses to feedback, enabling firms to avert negative brand experiences, and improve overall customer engagement.

The research intends to give insight into how sentiment analysis by AI, specifically through Gemini, can improve customer experience and assist restaurants in making informed decisions.