Social media analytics and value creation in urban smart tourism ecosystems

In this article, we demonstrate the potential value that the spatial and semantic analysis of social media messages can provide to smart tourism ecosystems. Building upon a showcase of 600,000 Twitter messages in San Francisco, we illustrate insights for stakeholders within the tourism sector from various analyses, including kernel density estimation and latent Dirichlet allocation. We show that social media analytics captures spatial patterns within the city that relate to the presence of users and the environmental and topical engagement. Furthermore, we outline how these patterns serve as an input to value creation for smart urban tourism.

[1]  Jun Yan,et al.  Kernel Density Estimation of traffic accidents in a network space , 2008, Comput. Environ. Urban Syst..

[2]  Changsok Yoo,et al.  An analysis of the utilization of Facebook by local Korean governments for tourism development and the network of smart tourism ecosystem , 2016, Int. J. Inf. Manag..

[3]  Richard T. Watson,et al.  Location-based services , 2008, CACM.

[4]  Roman Beck,et al.  Effectiveness of corporate social media activities in increasing relational outcomes , 2015, Inf. Manag..

[5]  Jiafeng Guo,et al.  BTM: Topic Modeling over Short Texts , 2014, IEEE Transactions on Knowledge and Data Engineering.

[6]  M. Broersma,et al.  TWITTER AS A NEWS SOURCE , 2013 .

[7]  J. Byers,et al.  The Rise of the Sharing Economy: Estimating the Impact of Airbnb on the Hotel Industry , 2017 .

[8]  Chulmo Koo,et al.  Adoption of travel information in user-generated content on social media: the moderating effect of social presence , 2015, Behav. Inf. Technol..

[9]  Ana María Munar,et al.  Trust and Involvement in Tourism Social Media and Web-Based Travel Information Sources , 2013 .

[10]  C. D. Kemp,et al.  Density Estimation for Statistics and Data Analysis , 1987 .

[11]  Matthew S. Gerber,et al.  Predicting crime using Twitter and kernel density estimation , 2014, Decis. Support Syst..

[12]  Stefan Stieglitz,et al.  Social Media Analytics , 2014 .

[13]  D. Fesenmaier,et al.  Sharing Tourism Experiences , 2017 .

[14]  E. Marcheggiani,et al.  Mapping Cilento: Using geotagged social media data to characterize tourist flows in southern Italy , 2016 .

[15]  Piera Buonincontri,et al.  The experience co-creation in smart tourism destinations: a multiple case analysis of European destinations , 2016, J. Inf. Technol. Tour..

[16]  Ana María Munar,et al.  Motivations for sharing tourism experiences through social media , 2014 .

[17]  Dirk Neumann,et al.  Data Analytics for Location-Based Services: Enabling User-Based Relocation of Carsharing Vehicles , 2015, ICIS.

[18]  Weiguo Fan,et al.  The power of social media analytics , 2014, CACM.

[19]  Rein Ahas,et al.  Measuring tourism destinations using mobile tracking data , 2016 .

[20]  C Weidemann.  Social Media Location Intelligence: The Next Privacy Battle - An ArcGIS add-in and Analysis of Geospatial Data Collected from Twitter.com , 2013 .

[21]  Richard T. Watson,et al.  Smart Cities and the Role of IS Research in Improving Urban Life , 2016, ICIS.

[22]  A. Fleischer,et al.  The Role of Cybermediaries in Reputation Building and Price Premiums in the Online Hotel Market , 2012 .

[23]  Ling Chen,et al.  A context-aware personalized travel recommendation system based on geotagged social media data mining , 2013, Int. J. Geogr. Inf. Sci..

[24]  A. Bruns,et al.  Twitter and Society , 2013 .

[25]  Alexander Zipf,et al.  An Advanced Systematic Literature Review on Spatiotemporal Analyses of Twitter Data , 2015, Trans. GIS.

[26]  Carlo Ratti,et al.  Geo-located Twitter as proxy for global mobility patterns , 2013, Cartography and geographic information science.

[27]  David B. Dunson,et al.  Probabilistic topic models , 2011, KDD '11 Tutorials.

[28]  S. Travis Waller,et al.  Utilising Location Based Social Media in Travel Survey Methods: bringing Twitter data into the play , 2015, LBSN@SIGSPATIAL/GIS.

[29]  Ulrike Gretzel,et al.  Smart tourism: foundations and developments , 2015, Electronic Markets.

[30]  Tracy L. Tuten,et al.  Social media picture posting and souvenir purchasing behavior: Some initial findings , 2013 .

[31]  Chulmo Koo,et al.  The use of social media in travel information search , 2015, Telematics Informatics.

[32]  P. Gerbaudo.  Tweets and the Streets: Social Media and Contemporary Activism , 2012 .

[33]  Weiguo Fan,et al.  Novel applications of social media analytics , 2015, Inf. Manag..

[34]  Detlef Schoder,et al.  Mineable or messy? Assessing the quality of macro-level tourism information derived from social media , 2015, Electron. Mark..

[35]  Rob Law,et al.  Tourism and online photography , 2011 .

[36]  B. Silverman.  Density estimation for statistics and data analysis , 1986 .

[37]  Ulrike Gretzel,et al.  Conceptual foundations for understanding smart tourism ecosystems , 2015, Comput. Hum. Behav..

[38]  Kurt Hornik,et al.  topicmodels : An R Package for Fitting Topic Models , 2016 .

[39]  Josep Blat,et al.  Digital Footprinting: Uncovering Tourists with User-Generated Content , 2008, IEEE Pervasive Computing.

[40]  C. Pedron,et al.  Analysing reviews in the Web 2.0: Small and medium hotels in Portugal , 2012 .

[41]  Felix Kling,et al.  When a city tells a story: urban topic analysis , 2012, SIGSPATIAL/GIS.

[42]  R. Levine,et al.  The Pace of Life in 31 Countries , 1999 .

[43]  Johannes Bendler,et al.  Taming Uncertainty in Big Data , 2014, Bus. Inf. Syst. Eng..

[44]  Maria Banyai,et al.  Social media in travel, tourism, and hospitality: Theory, Practice and cases , 2012 .

[45]  A. Guerry,et al.  Using social media to quantify nature-based tourism and recreation , 2013, Scientific Reports.