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This article examines restaurant customers’ online activity following visits to restaurants. Differences in customers’ opinions based on gender and location are discussed. Sentiment analysis was used to analyze customers’ social media behavior in terms of liking, rating, and reviewing restaurants. User‐generated reviews and comments about experiences influence potential customers’ decisions. The results of this study show that gender and location of customers influence restaurant ratings. This article shows that sentiment analysis (using Natural Language Toolkit and TextBlob) can help marketers by providing a useful tool for big data analysis. Sentiment analysis can be used to interpret customer behavior and highlight how presales, sales, and after‐sales strategies can be improved.

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