Based on a successful Tourism Analytics session held within AAG2018, 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 (Andrei.Kirilenko@ufl.edu) and Jin-Won Kim (JinWonKim@ufl.edu) prior to the deadline of November 8, 2018. 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)
|Presenter||Andrei P. Kirilenko*, University of Florida, Svetlana O. Stepchenkova, University of Florida, Juan M. Hernández, University of Las Palmas de Gran Canaria, Tourist segmentation through network analysis of user generated content||20||1:10 PM|
|Presenter||Svetlana Stepchenkova*, , Andrei P. Kirilenko, University of Florida, Juan M. Hernández, University of Las Palmas de Gran Canaria, Comparing Tourism Clusters with Network and Spatial Analyses of Online Reviews||20||1:30 PM|
|Presenter||Yang Yang*, Temple University, Xiaowei Zhang, Harbin Institute of Technology, Yi Zhang, Peking University, Tourists' behavior and experience under air pollution||20||1:50 PM|
|Presenter||Grant McKenzie*, McGill University, Toronto's Eiffel Tower: Assessing tourist attraction similarities through user-contributed content||20||2:10 PM|
|Presenter||Luyu Wang*, University of Florida, Angélica Almeyda Zambrano, University of Florida, Zhaohe Xu, Amazon.com, Inc , Mining Online User-Generated Content: Investigating Travel Experiences in Manuel Antonio National Park||20||2:30 PM|
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