Analyzing and Responding to Google Maps Reviews with a Chatbot in Healthcare

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dc.authorscopusid57219132759
dc.authorscopusid57202924825
dc.contributor.authorAkkol E.
dc.contributor.authorDogan O.
dc.date.accessioned2024-03-09T19:39:55Z
dc.date.available2024-03-09T19:39:55Z
dc.date.issued2023
dc.departmentİzmir Bakırçay Üniversitesien_US
dc.descriptionIntelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference -- 22 August 2023 through 24 August 2023 -- -- 299549en_US
dc.description.abstractThis paper aims to explore how Google Maps reviews for an education and research hospital can be analyzed and responded to using a chatbot. The study highlights the importance of customer feedback in improving hospital services and describes how classification algorithms can be used to collect and analyze reviews. It compares five algorithms to analyze reviews. The chatbot designed in this study responds to reviews and offers personalized suggestions to patients using the most accurate one among five algorithms. The findings suggest that automated chatbot responses can save time and resources while improving the hospital’s online reputation. The study concludes that implementing a chatbot for Google Maps reviews can enhance patient satisfaction and lead to better overall service quality. Among the five classification algorithms used within the scope of the study, it was determined that Naive Bayes and Neural Networks algorithms gave the highest accuracy rate with 79% when categorizing the comments according to the subject and performing the sentiment analysis at the same time. However, other algorithms’ success rates are similar, and the chatbot responds to people by using the results of the algorithm with the highest success rate for each newly entered sentence. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.en_US
dc.identifier.doi10.1007/978-3-031-39777-6_14
dc.identifier.endpage123en_US
dc.identifier.isbn9783031397769
dc.identifier.issn2367-3370
dc.identifier.scopus2-s2.0-85172738792en_US
dc.identifier.scopusqualityQ4en_US
dc.identifier.startpage116en_US
dc.identifier.urihttps://doi.org/10.1007/978-3-031-39777-6_14
dc.identifier.urihttps://hdl.handle.net/20.500.14034/1553
dc.identifier.volume759 LNNSen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.relation.ispartofLecture Notes in Networks and Systemsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectChatbot; Google maps reviews; Healthcare; Sentiment analysis; Text miningen_US
dc.subjectHealth care; Hospitals; Chatbots; Classification algorithm; Customer feedback; Education and researches; Google map review; Google maps; Healthcare; Hospital service; Sentiment analysis; Text-mining; Sentiment analysisen_US
dc.titleAnalyzing and Responding to Google Maps Reviews with a Chatbot in Healthcareen_US
dc.typeConference Objecten_US

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