AI and Big Data in Tourism and Hospitality 1: social media, spatially distributed data and data mining
Type: Virtual Paper
Day: 2/28/2022
Start Time: 2:00 PM
End Time: 3:20 PM
Theme:
Sponsor Group(s):
Recreation, Tourism, and Sport Specialty Group
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Organizer(s):
Andrei Kirilenko
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Chairs(s):
Andrei Kirilenko, University of Florida
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Description:
This session invites innovative advanced data intensive research on tourism-related issues with the goal of exchanging ideas, new approaches, and forming potential collaborations. The data revolution, which started during the past decade, brought new possibilities for decision making and innovation based on the novel methods of analysis of (typically) very large sets of data. Tourism analytics is a new area. Evidentially, the field is highly fragmented, the methods to analyze data are not firmly set, are still evolving and very fluid. We invite submissions in tourism analytics, including but not limiting to the following topics:
• Spatial data analysis and visualization with GIS and other geospatial technologies and models (GPS, RS, LiDAR, digital traces, etc.). This includes mapping of tourist routes, tourist flows, travel photo locations, geo-locations of tweets, emotional mapping, and other spatially distributed social data.
• Analysis of social media (Twitter, Facebook, Instagram and similar platforms), online customer reviews, tourist experiences reported online and other user-generated content.
• Analysis of unstructured data: text analysis, sentiment analysis, analysis of photographs and video.
• People as sensors (digital traces, big data from sensory experiences, Google glasses and similar technologies).
We welcome papers covering data intensive applications in tourism, hospitality, and recreation.
Presentation(s), if applicable
Andrei Kirilenko, University of Florida; Mining travelers' reviews on social media: one platform is not enough. |
Lijuan SU, ; Typology and Crisis Response Strategies of Sports Games Online Crises |
Yuting An, University of Florida; Exploring evacuation patterns during Hurricane Irma: the differences between residents and tourists |
Shengye Wang, ; Spatiotemporal Heterogeneity of Hotel Daily Rates under the Temporary Lockdown in Xi’an City of China |
Non-Presenting Participants Agenda
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AI and Big Data in Tourism and Hospitality 1: social media, spatially distributed data and data mining
Description
Virtual Paper
Contact the Primary Organizer
Andrei Kirilenko - andrei.kirilenko@ufl.edu
Session Sponsored By
