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Paper Type
ERF
Description
Yelp is an online social network service in which consumers provide reviews on their local business restaurants. Because our data is in the form of human review text, this study utilizes natural language processing (NLP) and machine learning (ML) to vectorize the text reviews and apply sentiment analysis through logistic regression. After optimizing the model parameters, sentiments of popular restaurants in Los Angeles before and during COVID-19 are analyzed. Latent Semantic Analysis (LSA) and topic modeling used to gather the topics of reviews and logistic regression is used for feature importance. Data is extracted from available Yelp reviews of restaurants and includes total of 10,390 reviews. Results explain a difference in the number of reviews, sentiments, and the content before and during the COVID-19. This study provides insights for both theory and practice and shed light into the restaurant industry challenges during the global pandemic.
Paper Number
1966
Recommended Citation
Koohikamali, Mehrdad, "Restaurant Industry Revival or Death: How Do Reviews Change During COVID-19?" (2023). AMCIS 2023 Proceedings. 18.
https://aisel.aisnet.org/amcis2023/sig_dsa/sig_dsa/18
Restaurant Industry Revival or Death: How Do Reviews Change During COVID-19?
Yelp is an online social network service in which consumers provide reviews on their local business restaurants. Because our data is in the form of human review text, this study utilizes natural language processing (NLP) and machine learning (ML) to vectorize the text reviews and apply sentiment analysis through logistic regression. After optimizing the model parameters, sentiments of popular restaurants in Los Angeles before and during COVID-19 are analyzed. Latent Semantic Analysis (LSA) and topic modeling used to gather the topics of reviews and logistic regression is used for feature importance. Data is extracted from available Yelp reviews of restaurants and includes total of 10,390 reviews. Results explain a difference in the number of reviews, sentiments, and the content before and during the COVID-19. This study provides insights for both theory and practice and shed light into the restaurant industry challenges during the global pandemic.
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