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Analyzing user sentiment in social media: Implications for online marketing strategy
Author(s) -
Micu Adrian,
Micu Angela Eliza,
Geru Marius,
Lixandroiu Radu Constantin
Publication year - 2017
Publication title -
psychology and marketing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.035
H-Index - 116
eISSN - 1520-6793
pISSN - 0742-6046
DOI - 10.1002/mar.21049
Subject(s) - sentiment analysis , social media , social media marketing , marketing , advertising , computer science , business , world wide web , artificial intelligence
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.