Improving Restaurants' Business Performance Using Yelp Data Sets through Sentiment Analysis-Reference-Cited by-同舟云学术

Improving Restaurants' Business Performance Using Yelp Data Sets through Sentiment Analysis

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2019 3rd International Conference on E-commerce, E-Business and E-Government - ICEEG 2019
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Author:

Ching Michelle Renee D.¹,de Dios Bulos Remedios¹

Affiliation:

1. College of Computer Studies, De La Salle University, Manila, Philippines

Publisher

ACM Press

Reference17 articles.

1. Alexandra Amado, Paulo Cortez, Paulo Rita, and Sérgio Moro. 2017. Research Trends on Big Data in Marketing: A Text Mining and Topic Modeling Based Literature Analysis. Eur. Res. Manag. Bus. Econ. (2017). DOI:https://doi.org/10.1016/j.iedeen.2017.06.002

2. Yue Guo, Stuart J. Barnes, and Qiong Jia. 2017. Mining Meaning from Online Ratings and Reviews: Tourist Satisfaction Analysis Using Latent Dirichlet Allocation. Tour. Manag. 59, (2017), 467--483. DOI:https://doi.org/10.1016/j.tourman.2016.09.009

3. Bryan Hood, Victor Hwang, and Jennifer King. 2013. Inferring Future Business Attention. In Yelp Challenge. Retrieved from http://www.yelp.com/html/pdf/YelpDatasetChallengeWinner_InferringFuture.pdf

4. James Huang, Stephanie Rogers, and Eunkwang Joo. 2014. Improving Restaurants by Extracting Subtopics from Yelp Reviews. In iConference 2014 Berlin, 1--5. Retrieved from https://www.ideals.illinois.edu/handle/2142/48832

5. Manish Kacker and Rozenn Perrigot. 2016. Retailer use of a professional social media network: Insights from franchising. J. Retail. Consum. Serv. 30, (2016), 222--233. DOI:https://doi.org/10.1016/j.jretconser.2016.01.020

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