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Big Data Improves Visitor Experience at Local, State, and National Parks—Natural Language Processing Applied to Customer Feedback

Chapter
Part of the Studies in Big Data book series (SBD, volume 42)

Abstract

Local, State and National parks are a major source of natural beauty, fresh air, and calming environs that are being used more and more by visitors to achieve mental and physical wellbeing. Given the popularity of social networks and availability of smartphones with user-friendly apps, these patrons are recording their visit experiences in the form of online reviews and blogs. The availability of this voluminous data provides an excellent opportunity for facility management to improve their service operation by cherishing the positive compliments and identifying and addressing the inherent concerns. This data however, lacks structure, is voluminous and is not easily amenable to manual analysis necessitating the use of Big Data approaches. We designed, developed, and implemented software systems that can download, organize, and analyze the text from these online reviews, analyze them using Natural Language Processing algorithms to perform sentiment analysis and topic modeling and provide facility managers actionable insights to improve visitor experience.

Notes

Acknowledgements

This research was conducted at the New York State Water Resources Institute and funded by the Hudson River Estuary Program, a program of the NYS Department of Environmental Conservation. We are grateful for the support we received from those two organizations on the intellectual, educational, technological, motivational, and financial dimensions.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Samuel Curtis Johnson Graduate School of ManagementCornell UniversityIthacaUSA

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