Systematic Contextual-based Affinity Analytics Research on Association of Manager Response and Customer Reviews

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dc.contributor.author Babu, Xavier
dc.contributor.author Zhang, Juheng
dc.date.accessioned 2023-12-26T18:38:46Z
dc.date.available 2023-12-26T18:38:46Z
dc.date.issued 2024-01-03
dc.identifier.isbn 978-0-9981331-7-1
dc.identifier.other f0c03864-8346-4a11-8351-bd9daa023bf6
dc.identifier.uri https://hdl.handle.net/10125/106692
dc.language.iso eng
dc.relation.ispartof Proceedings of the 57th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Data Analytics, Data Mining, and Machine Learning for Social Media
dc.subject affinity analytics
dc.subject contextual embedding.
dc.subject panel vector autoregression
dc.subject review convergence
dc.subject semantic text analytics
dc.title Systematic Contextual-based Affinity Analytics Research on Association of Manager Response and Customer Reviews
dc.type Conference Paper
dc.type.dcmi Text
dcterms.abstract We study the similarity between managers' responses and customer reviews and explore its influence on review convergence, customer ratings, and prices. While previous research has explored the influence of product reviews on price and reputation, little attention has been given to the effectiveness of managers' responses and their impact on product price and rating. This study fills this gap by examining managers' responses and their relationship with product review convergence/divergence. Additionally, we investigate whether managers exhibit similar responses to their peers and whether their responses are tailored to specific product review issues or broadly resemble their past responses. We develop a deep learning framework to understand semantic textual information in managers' responses and analyze the semantic affinity score with reviews. We investigate the dynamic relationships among managers' responses, product reviews, review convergence, product reputation and price with the Panel Vector Autoregression model with a travel dataset from TripAdvisor.com.
dcterms.extent 10 pages
prism.startingpage 2563
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