Tourism analytics: social media, spatially distributed data and data mining in tourism research

Type: Paper
Sponsor Groups: Recreation, Tourism, and Sport Specialty Group
Poster #:
Day: 4/9/2020
Start / End Time: 4:55 PM / 6:10 PM
Room: Tower Court B, Sheraton, IM Pei Tower, Second Floor Level
Organizers: Andrei Kirilenko, Yang Yang
Chairs: Andrei Kirilenko

Call for Submissions

Based on a successful Tourism Analytics session held within AAG-2019 and 2018, we are inviting oral presentations on data intensive and spatial analysis in tourism with particular interest in data mining, text mining, image recognition, user-generated content, GIS analysis and similar application outlined in Description section. This session is targeting innovative advanced data intensive research in tourism with the goal of exchanging ideas, new approaches, and potential collaborations. Please e-mail paper titles and abstracts to session organizers Andrei Kirilenko ( and Yang Yang ( prior to the deadline. Abstracts may not exceed 250 words.


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) vary large sets of data. Tourism Analytics is a new area in tourism research and education. Evidentially, the field is highly fragmented, the methods to analyze data are not firmly set, are still evolving and very fluid. However, the following common key areas, and methods emerge:
• Spatial data analysis and visualization with GIS. Includes mapping of tourist routes, travel photo locations, geo-locations of tweets, 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. Involves network analysis, data mining and text analysis.
• Analysis of unstructured data: text analysis, analysis of photos and videos
• Sentiment analysis: one of the most active research areas in natural language processing, web/social network mining, and text/multimedia data mining.
• People as sensors (digital traces, big data from sensory experiences, Google glasses and such)


Type Details Minutes Start Time
Presenter Andrei Kirilenko*, University of Florida, Svetlana Stepchenkova, University of Florida, Topic modeling of negative reviews on TripAdvisor 15 4:55 PM
Presenter Yang Yang*, Temple University, A big data analytics of nocturnal tourists 15 5:10 PM
Presenter Lijuan Su*, University of Florida, Svetlana Stepchenkova, University of Florida, The information transmissions dynamics of online firestorm: 5-star hotel hygiene horror on Sina Weibo 15 5:25 PM
Presenter Luyu Wang*, University of Florida, Angélica Almeyda Zambrano, University of Florida, Zhaohe Xu,, Inc, Culture and Travel Experience in Natural Environments from Online User-Generated Content: The Grand Canyon National Park 15 5:40 PM
Presenter Shihan Ma*, University of Florida, Andrei Kirilenko, University of Florida, Lijuan Su, University of Florida, Review of tourism-oriented travel based on social media data 15 5:55 PM

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