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2021 | OriginalPaper | Buchkapitel

Modeling Tourism Using Spatial Analysis Based on Social Media Big Data: A Review

verfasst von : Zhu Chen, Rayner Alfred, Oliver Valentine Eboy

Erschienen in: Computational Science and Technology

Verlag: Springer Singapore

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Abstract

Since an ever-increasing part of the population makes use of social media in their day-to-day lives, social media data has been analyzed in many different disciplines. While there is a great deal of literature on the challenges and difficulties involving specific data analysis methods, there hardly exists research on analyzing the appropriate techniques used to handle different types of data for the purpose of social media analytics. To address this gap, we conducted an extended and structured literature analysis through which we identified challenges addressed and solutions proposed. The literature search revealed that three types of data that were least used for social media analytics that includes Bluetooth, WIFI and mobile roaming data. In contrast, other types of data have received more attention. Based on the results of the literature search, we discuss the most important challenges for researchers and present potential solutions. The findings are used to extend an existing framework on social media analytics. The article provides benefits for researchers and practitioners who wish to collect and analysis social media data.

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Literatur
1.
Zurück zum Zitat Hua LY, Ramayah T, Ping TA, Jun-Hwa C (2017) Social media as a tool to help select tourism destinations: the case of Malaysia. Inf Syst Manag 34(3):265–279CrossRef Hua LY, Ramayah T, Ping TA, Jun-Hwa C (2017) Social media as a tool to help select tourism destinations: the case of Malaysia. Inf Syst Manag 34(3):265–279CrossRef
2.
Zurück zum Zitat Berno T, Ward C (2005) Innocence abroad: a pocket guide to psychological research on tourism. Am Psychol 60(6):593–600CrossRef Berno T, Ward C (2005) Innocence abroad: a pocket guide to psychological research on tourism. Am Psychol 60(6):593–600CrossRef
3.
Zurück zum Zitat Kim J, Fesenmaier DR (2017) Sharing tourism experiences: the posttrip experience. J Travel Res 56(1):28–40CrossRef Kim J, Fesenmaier DR (2017) Sharing tourism experiences: the posttrip experience. J Travel Res 56(1):28–40CrossRef
4.
Zurück zum Zitat DeAndrea DC, Ellison NB, LaRose R, Steinfield C, Fiore A (2012) Serious social media: on the use of social media for improving students’ adjustment to college. The Intern High Educ 15(1):15–23CrossRef DeAndrea DC, Ellison NB, LaRose R, Steinfield C, Fiore A (2012) Serious social media: on the use of social media for improving students’ adjustment to college. The Intern High Educ 15(1):15–23CrossRef
5.
Zurück zum Zitat Liu DJ, Hu J, Cheng SW, Chen JZ, Zhang Q (2015) Spatial distribution pattern and influencing factors of China’s tourism Weibo——taking Sina Travel Weibo as an example. Scientia Geographica Sinica 35(06):717–724 Liu DJ, Hu J, Cheng SW, Chen JZ, Zhang Q (2015) Spatial distribution pattern and influencing factors of China’s tourism Weibo——taking Sina Travel Weibo as an example. Scientia Geographica Sinica 35(06):717–724
6.
Zurück zum Zitat Kambatla K, Kollias G, Kumar V, Grama A (2014) Trends in big data analytics. J Parall Distrib Comput 74(7):2561–2573CrossRef Kambatla K, Kollias G, Kumar V, Grama A (2014) Trends in big data analytics. J Parall Distrib Comput 74(7):2561–2573CrossRef
7.
Zurück zum Zitat Rashidi TH, Abbasi A, Maghrebi M, Hasan S, Waller TS (2017) Exploring the capacity of social media data for modelling travel behaviour: opportunities and challenges. Transp Res Part C: Emerg Technol 75:197–211CrossRef Rashidi TH, Abbasi A, Maghrebi M, Hasan S, Waller TS (2017) Exploring the capacity of social media data for modelling travel behaviour: opportunities and challenges. Transp Res Part C: Emerg Technol 75:197–211CrossRef
8.
Zurück zum Zitat Schuckert M, Liu X, Law R (2015) Hospitality and tourism online reviews: recent trends and future directions. J Travel Tour Market 32(5):608–621CrossRef Schuckert M, Liu X, Law R (2015) Hospitality and tourism online reviews: recent trends and future directions. J Travel Tour Market 32(5):608–621CrossRef
9.
Zurück zum Zitat Shoval N, Ahas R (2016) The use of tracking technologies in tourism research: the first decade. Tour Geogr 18(5):587–606CrossRef Shoval N, Ahas R (2016) The use of tracking technologies in tourism research: the first decade. Tour Geogr 18(5):587–606CrossRef
10.
Zurück zum Zitat Guo Y, Barnes SJ, Jia Q (2017) Mining meaning from online ratings and reviews: tourist satisfaction analysis using latent dirichlet allocation. Tour Manag 59:467–483CrossRef Guo Y, Barnes SJ, Jia Q (2017) Mining meaning from online ratings and reviews: tourist satisfaction analysis using latent dirichlet allocation. Tour Manag 59:467–483CrossRef
11.
Zurück zum Zitat Liu Y, Teichert T, Rossi M, Li H, Hu F (2017) Big data for big insights: investigating language-specific drivers of hotel satisfaction with 412,784 user-generated reviews. Tour Manag 59:554–563CrossRef Liu Y, Teichert T, Rossi M, Li H, Hu F (2017) Big data for big insights: investigating language-specific drivers of hotel satisfaction with 412,784 user-generated reviews. Tour Manag 59:554–563CrossRef
12.
Zurück zum Zitat Xiang Z, Schwartz Z, Gerdes JH Jr, Uysal M (2015) What can big data and text analytics tell us about hotel guest experience and satisfaction? Int J Hosp Manag 44:120–130CrossRef Xiang Z, Schwartz Z, Gerdes JH Jr, Uysal M (2015) What can big data and text analytics tell us about hotel guest experience and satisfaction? Int J Hosp Manag 44:120–130CrossRef
13.
Zurück zum Zitat Xu X, Li Y (2016) The antecedents of customer satisfaction and dissatisfaction toward various types of hotels: a text mining approach. Int J Hosp Manag 55:57–69CrossRef Xu X, Li Y (2016) The antecedents of customer satisfaction and dissatisfaction toward various types of hotels: a text mining approach. Int J Hosp Manag 55:57–69CrossRef
14.
Zurück zum Zitat Yuan H, Xu H, Qian Y, Li Y (2016) Make your travel smarter: summarizing urban tourism information from massive blog data. Int J Inf Manage 36(6):1306–1319CrossRef Yuan H, Xu H, Qian Y, Li Y (2016) Make your travel smarter: summarizing urban tourism information from massive blog data. Int J Inf Manage 36(6):1306–1319CrossRef
15.
Zurück zum Zitat Philander K, Zhong Y (2016) Twitter sentiment analysis: capturing sentiment from integrated resort tweets. Int J Hosp Manag 55(2016):16–24CrossRef Philander K, Zhong Y (2016) Twitter sentiment analysis: capturing sentiment from integrated resort tweets. Int J Hosp Manag 55(2016):16–24CrossRef
16.
Zurück zum Zitat Da Rugna J, Chareyron G, Branchet B (2012) Tourist behavior analysis through geotagged photographies: a method to identify the country of origin. In: 2012 IEEE 13th international symposium on computational intelligence and informatics (CINTI). IEEE, pp 347–351 Da Rugna J, Chareyron G, Branchet B (2012) Tourist behavior analysis through geotagged photographies: a method to identify the country of origin. In: 2012 IEEE 13th international symposium on computational intelligence and informatics (CINTI). IEEE, pp 347–351
17.
Zurück zum Zitat Lu D, Wu R, Sang J (2017) Overlapped user-based comparative study on photo-sharing websites. Inf Sci 376:54–70CrossRef Lu D, Wu R, Sang J (2017) Overlapped user-based comparative study on photo-sharing websites. Inf Sci 376:54–70CrossRef
18.
Zurück zum Zitat Vu HQ, Li G, Law R, Ye BH (2015) Exploring the travel behaviors of inbound tourists to Hong Kong using geotagged photos. Tour Manag 46:222–232CrossRef Vu HQ, Li G, Law R, Ye BH (2015) Exploring the travel behaviors of inbound tourists to Hong Kong using geotagged photos. Tour Manag 46:222–232CrossRef
19.
Zurück zum Zitat Lee I, Cai G, Lee K (2014) Exploration of geo-tagged photos through data mining approaches. Expert Syst Appl 41(2):397–405CrossRef Lee I, Cai G, Lee K (2014) Exploration of geo-tagged photos through data mining approaches. Expert Syst Appl 41(2):397–405CrossRef
20.
Zurück zum Zitat Lu X, Wang C, Yang JM, Pang Y, Zhang L (2010) Photo2trip: generating travel routes from geo-tagged photos for trip planning. In: Proceedings of the 18th ACM international conference on multimedia. ACM, pp 143–152 Lu X, Wang C, Yang JM, Pang Y, Zhang L (2010) Photo2trip: generating travel routes from geo-tagged photos for trip planning. In: Proceedings of the 18th ACM international conference on multimedia. ACM, pp 143–152
21.
Zurück zum Zitat Deng N, Li XR (2018) Feeling a destination through the “right” photos: a machine learning model for DMOs’ photo selection. Tour Manag 65:267–278CrossRef Deng N, Li XR (2018) Feeling a destination through the “right” photos: a machine learning model for DMOs’ photo selection. Tour Manag 65:267–278CrossRef
22.
Zurück zum Zitat Bauder M, Freytag T (2015) Visitor mobility in the city and the effects of travel preparation. Tour Geogr 17(5):682–700CrossRef Bauder M, Freytag T (2015) Visitor mobility in the city and the effects of travel preparation. Tour Geogr 17(5):682–700CrossRef
23.
Zurück zum Zitat East D, Osborne P, Kemp S, Woodfine T (2017) Combining GPS & survey data improves understanding of visitor behaviour. Tour Manag 61:307–320CrossRef East D, Osborne P, Kemp S, Woodfine T (2017) Combining GPS & survey data improves understanding of visitor behaviour. Tour Manag 61:307–320CrossRef
24.
Zurück zum Zitat Shoval N, McKercher B, Birenboim A, Ng E (2015) The application of a sequence alignment method to the creation of typologies of tourist activity in time and space. Environ Plann B: Plann Des 42(1):76–94CrossRef Shoval N, McKercher B, Birenboim A, Ng E (2015) The application of a sequence alignment method to the creation of typologies of tourist activity in time and space. Environ Plann B: Plann Des 42(1):76–94CrossRef
25.
Zurück zum Zitat Zakrisson I, Zillinger M (2012) Emotions in motion: tourist experiences in time and space. Curr Issues Tour 15(6):505–523CrossRef Zakrisson I, Zillinger M (2012) Emotions in motion: tourist experiences in time and space. Curr Issues Tour 15(6):505–523CrossRef
26.
Zurück zum Zitat Zheng W, Huang X, Li Y (2017) Understanding the tourist mobility using GPS: where is the next place? Tour Manag 59:267–280CrossRef Zheng W, Huang X, Li Y (2017) Understanding the tourist mobility using GPS: where is the next place? Tour Manag 59:267–280CrossRef
27.
Zurück zum Zitat Ahas R, Aasa A, Roose A, Mark Ü, Silm S (2008) Evaluating passive mobile positioning data for tourism surveys: an Estonian case study. Tour Manag 29(3):469–486CrossRef Ahas R, Aasa A, Roose A, Mark Ü, Silm S (2008) Evaluating passive mobile positioning data for tourism surveys: an Estonian case study. Tour Manag 29(3):469–486CrossRef
28.
Zurück zum Zitat Raun J, Ahas R, Tiru M (2016) Measuring tourism destinations using mobile tracking data. Tour Manag 57:202–212CrossRef Raun J, Ahas R, Tiru M (2016) Measuring tourism destinations using mobile tracking data. Tour Manag 57:202–212CrossRef
29.
Zurück zum Zitat Nilbe K, Ahas R, Silm S (2014) Evaluating the travel distances of events visitors and regular visitors using mobile positioning data: the case of Estonia. J Urban Technol 21(2):91–107CrossRef Nilbe K, Ahas R, Silm S (2014) Evaluating the travel distances of events visitors and regular visitors using mobile positioning data: the case of Estonia. J Urban Technol 21(2):91–107CrossRef
30.
Zurück zum Zitat Ahas R, Aasa A, Mark Ü, Pae T, Kull A (2007) Seasonal tourism spaces in Estonia: case study with mobile positioning data. Tour Manag 28(3):898–910CrossRef Ahas R, Aasa A, Mark Ü, Pae T, Kull A (2007) Seasonal tourism spaces in Estonia: case study with mobile positioning data. Tour Manag 28(3):898–910CrossRef
31.
Zurück zum Zitat Versichele M, De Groote L, Bouuaert MC, Neutens T, Moerman I, Van de Weghe N (2014) Pattern mining in tourist attraction visits through association rule learning on Bluetooth tracking data: a case study of Ghent, Belgium. Tour Manag 44:67–81CrossRef Versichele M, De Groote L, Bouuaert MC, Neutens T, Moerman I, Van de Weghe N (2014) Pattern mining in tourist attraction visits through association rule learning on Bluetooth tracking data: a case study of Ghent, Belgium. Tour Manag 44:67–81CrossRef
32.
Zurück zum Zitat Yoshimura Y, Sobolevsky S, Ratti C, Girardin F, Carrascal JP, Blat J, Sinatra R (2014) An analysis of visitors’ behavior in the Louvre Museum: a study using Bluetooth data. Environ Plann B: Plann Des 41(6):1113–1131CrossRef Yoshimura Y, Sobolevsky S, Ratti C, Girardin F, Carrascal JP, Blat J, Sinatra R (2014) An analysis of visitors’ behavior in the Louvre Museum: a study using Bluetooth data. Environ Plann B: Plann Des 41(6):1113–1131CrossRef
33.
Zurück zum Zitat Bonné B, Barzan A, Quax P, Lamotte W (2013) WiFiPi: involuntary tracking of visitors at mass events. In: 2013 IEEE 14th international symposium on “A world of wireless, mobile and multimedia networks” (WoWMoM). IEEE, pp 1–6 Bonné B, Barzan A, Quax P, Lamotte W (2013) WiFiPi: involuntary tracking of visitors at mass events. In: 2013 IEEE 14th international symposium on “A world of wireless, mobile and multimedia networks” (WoWMoM). IEEE, pp 1–6
34.
Zurück zum Zitat Chilipirea C, Petre AC, Dobre C, van Steen M (2016) Presumably simple: monitoring crowds using WiFi. In: 2016 17th IEEE International Conference on Mobile Data Management (MDM) vol 1. IEEE, pp 220–225 Chilipirea C, Petre AC, Dobre C, van Steen M (2016) Presumably simple: monitoring crowds using WiFi. In: 2016 17th IEEE International Conference on Mobile Data Management (MDM) vol 1. IEEE, pp 220–225
35.
Zurück zum Zitat Li X, Wu Q, Peng G, Lv B (2016) Tourism forecasting by search engine data with noise-processing. Afr J Bus Manage 10(6):114–130CrossRef Li X, Wu Q, Peng G, Lv B (2016) Tourism forecasting by search engine data with noise-processing. Afr J Bus Manage 10(6):114–130CrossRef
36.
Zurück zum Zitat Bangwayo-Skeete PF, Skeete RW (2015) Can Google data improve the forecasting performance of tourist arrivals? Mixed-data sampling approach. Tour Manag 46:454–464CrossRef Bangwayo-Skeete PF, Skeete RW (2015) Can Google data improve the forecasting performance of tourist arrivals? Mixed-data sampling approach. Tour Manag 46:454–464CrossRef
37.
Zurück zum Zitat Gunter U, Önder I (2016) Forecasting city arrivals with Google analytics. Ann Tour Res 61:199–212CrossRef Gunter U, Önder I (2016) Forecasting city arrivals with Google analytics. Ann Tour Res 61:199–212CrossRef
38.
Zurück zum Zitat Huang X, Zhang L, Ding Y (2017) The Baidu index: uses in predicting tourism flows–a case study of the Forbidden City. Tour Manag 58:301–306CrossRef Huang X, Zhang L, Ding Y (2017) The Baidu index: uses in predicting tourism flows–a case study of the Forbidden City. Tour Manag 58:301–306CrossRef
39.
Zurück zum Zitat Li X, Pan B, Law R, Huang X (2017) Forecasting tourism demand with composite search index. Tour Manag 59:57–66CrossRef Li X, Pan B, Law R, Huang X (2017) Forecasting tourism demand with composite search index. Tour Manag 59:57–66CrossRef
40.
Zurück zum Zitat Park S, Lee J, Song W (2017) Short-term forecasting of Japanese tourist inflow to South Korea using Google trends data. J Travel Tour Market 34(3):357–368CrossRef Park S, Lee J, Song W (2017) Short-term forecasting of Japanese tourist inflow to South Korea using Google trends data. J Travel Tour Market 34(3):357–368CrossRef
41.
Zurück zum Zitat Peng G, Liu Y, Wang J, Gu J (2017) Analysis of the prediction capability of web search data based on the HE-TDC method-prediction of the volume of daily tourism visitors. J Syst Sci Syst Eng 26(2):163–182CrossRef Peng G, Liu Y, Wang J, Gu J (2017) Analysis of the prediction capability of web search data based on the HE-TDC method-prediction of the volume of daily tourism visitors. J Syst Sci Syst Eng 26(2):163–182CrossRef
42.
Zurück zum Zitat Rivera R (2016) A dynamic linear model to forecast hotel registrations in Puerto Rico using Google trends data. Tour Manag 57:12–20CrossRef Rivera R (2016) A dynamic linear model to forecast hotel registrations in Puerto Rico using Google trends data. Tour Manag 57:12–20CrossRef
43.
Zurück zum Zitat Yang X, Pan B, Evans JA, Lv B (2015) Forecasting Chinese tourist volume with search engine data. Tour Manag 46:386–397CrossRef Yang X, Pan B, Evans JA, Lv B (2015) Forecasting Chinese tourist volume with search engine data. Tour Manag 46:386–397CrossRef
44.
Zurück zum Zitat Choi H, Varian H (2012) Predicting the present with Google trends. Econ Rec 88:2–9CrossRef Choi H, Varian H (2012) Predicting the present with Google trends. Econ Rec 88:2–9CrossRef
45.
Zurück zum Zitat Pan B, Chenguang Wu D, Song H (2012) Forecasting hotel room demand using search engine data. J Hosp Tour Technol 3(3):196–210 Pan B, Chenguang Wu D, Song H (2012) Forecasting hotel room demand using search engine data. J Hosp Tour Technol 3(3):196–210
46.
Zurück zum Zitat Gawlik E, Kabaria H, Kaur S (2011) Predicting tourism trends with Google insights. Accessed December 1, 2012 Gawlik E, Kabaria H, Kaur S (2011) Predicting tourism trends with Google insights. Accessed December 1, 2012
47.
Zurück zum Zitat Saito T, Takahashi A, Tsuda H (2016) Optimal room charge and expected sales under discrete choice models with limited capacity. Int J Hosp Manag 57:116–131CrossRef Saito T, Takahashi A, Tsuda H (2016) Optimal room charge and expected sales under discrete choice models with limited capacity. Int J Hosp Manag 57:116–131CrossRef
48.
Zurück zum Zitat Falk M (2010) A dynamic panel data analysis of snow depth and winter tourism. Tour Manag 31(6):912–924CrossRef Falk M (2010) A dynamic panel data analysis of snow depth and winter tourism. Tour Manag 31(6):912–924CrossRef
49.
Zurück zum Zitat Kahn ME, Liu P (2016) Utilizing “Big Data” to improve the hotel sector’s energy efficiency: lessons from recent economics research. Cornell Hosp Quart 57(2):202–210CrossRef Kahn ME, Liu P (2016) Utilizing “Big Data” to improve the hotel sector’s energy efficiency: lessons from recent economics research. Cornell Hosp Quart 57(2):202–210CrossRef
50.
Zurück zum Zitat Plaza B (2011) Google analytics for measuring website performance. Tour Manag 32(3):477–481CrossRef Plaza B (2011) Google analytics for measuring website performance. Tour Manag 32(3):477–481CrossRef
51.
Zurück zum Zitat Sobolevsky S, Sitko I, Des Combes RT, Hawelka B, Arias JM, Ratti C (2014) Money on the move: Big data of bank card transactions as the new proxy for human mobility patterns and regional delineation. The case of residents and foreign visitors in Spain. In: 2014 IEEE international congress on big data. IEEE, pp 136–143 Sobolevsky S, Sitko I, Des Combes RT, Hawelka B, Arias JM, Ratti C (2014) Money on the move: Big data of bank card transactions as the new proxy for human mobility patterns and regional delineation. The case of residents and foreign visitors in Spain. In: 2014 IEEE international congress on big data. IEEE, pp 136–143
52.
Zurück zum Zitat Shih C, Nicholls S, Holecek DF (2009) Impact of weather on downhill ski lift ticket sales. J Travel Res 47(3):359–372CrossRef Shih C, Nicholls S, Holecek DF (2009) Impact of weather on downhill ski lift ticket sales. J Travel Res 47(3):359–372CrossRef
53.
Zurück zum Zitat Huang Z, Cao F, Jin C, Yu Z, Huang R (2017) Carbon emission flow from self-driving tours and its spatial relationship with scenic spots–a traffic-related big data method. J Clean Prod 142:946–955CrossRef Huang Z, Cao F, Jin C, Yu Z, Huang R (2017) Carbon emission flow from self-driving tours and its spatial relationship with scenic spots–a traffic-related big data method. J Clean Prod 142:946–955CrossRef
54.
Zurück zum Zitat Fang B, Ye Q, Kucukusta D, Law R (2016) Analysis of the perceived value of online tourism reviews: Influence of readability and reviewer characteristics. Tour Manag 52:498–506CrossRef Fang B, Ye Q, Kucukusta D, Law R (2016) Analysis of the perceived value of online tourism reviews: Influence of readability and reviewer characteristics. Tour Manag 52:498–506CrossRef
55.
Zurück zum Zitat Hu YH, Chen YL, Chou HL (2017) Opinion mining from online hotel reviews–a text summarization approach. Inf Process Manage 53(2):436–449CrossRef Hu YH, Chen YL, Chou HL (2017) Opinion mining from online hotel reviews–a text summarization approach. Inf Process Manage 53(2):436–449CrossRef
56.
Zurück zum Zitat Ma J, Luo S, Yao J, Cheng S, Chen X (2016) Efficient opinion summarization on comments with online-LDA. Int J Comput Commun Control 11(3):414–427CrossRef Ma J, Luo S, Yao J, Cheng S, Chen X (2016) Efficient opinion summarization on comments with online-LDA. Int J Comput Commun Control 11(3):414–427CrossRef
57.
Zurück zum Zitat Park S, Nicolau JL (2015) Asymmetric effects of online consumer reviews. Ann Tour Res 50:67–83CrossRef Park S, Nicolau JL (2015) Asymmetric effects of online consumer reviews. Ann Tour Res 50:67–83CrossRef
58.
Zurück zum Zitat Ye Q, Law R, Gu B (2009) The impact of online user reviews on hotel room sales. Int J Hosp Manag 28(1):180–182CrossRef Ye Q, Law R, Gu B (2009) The impact of online user reviews on hotel room sales. Int J Hosp Manag 28(1):180–182CrossRef
59.
Zurück zum Zitat Cheng M, Edwards D (2015) Social media in tourism: a visual analytic approach. Curr Issues Tour 18(11):1080–1087CrossRef Cheng M, Edwards D (2015) Social media in tourism: a visual analytic approach. Curr Issues Tour 18(11):1080–1087CrossRef
60.
Zurück zum Zitat Chua A, Servillo L, Marcheggiani E, Moere AV (2016) Mapping Cilento: using geotagged social media data to characterize tourist flows in southern Italy. Tour Manag 57:295–310CrossRef Chua A, Servillo L, Marcheggiani E, Moere AV (2016) Mapping Cilento: using geotagged social media data to characterize tourist flows in southern Italy. Tour Manag 57:295–310CrossRef
61.
Zurück zum Zitat Bordogna G, Frigerio L, Cuzzocrea A, Psaila G (2016) Clustering geo-tagged tweets for advanced big data analytics. In: 2016 IEEE international congress on Big Data (BigData congress). IEEE, pp 42–51 Bordogna G, Frigerio L, Cuzzocrea A, Psaila G (2016) Clustering geo-tagged tweets for advanced big data analytics. In: 2016 IEEE international congress on Big Data (BigData congress). IEEE, pp 42–51
62.
Zurück zum Zitat Brovelli MA, Minghini M, Zamboni G (2016) Public participation in GIS via mobile applications. ISPRS J Photogramm Remote Sens 114:306–315CrossRef Brovelli MA, Minghini M, Zamboni G (2016) Public participation in GIS via mobile applications. ISPRS J Photogramm Remote Sens 114:306–315CrossRef
63.
Zurück zum Zitat Freeman L (2004) The development of social network analysis. A Study in the Sociology of Science, 1, 687 Freeman L (2004) The development of social network analysis. A Study in the Sociology of Science, 1, 687
64.
Zurück zum Zitat Peuquet DJ (1994) It’s about time: a conceptual framework for the representation of temporal dynamics in geographic information systems. Ann Assoc Am Geogr 84(3):441–461CrossRef Peuquet DJ (1994) It’s about time: a conceptual framework for the representation of temporal dynamics in geographic information systems. Ann Assoc Am Geogr 84(3):441–461CrossRef
65.
Zurück zum Zitat Bertin J (1983) Semiology of graphics: diagrams. Networks, Maps 10(00690805.1987), 10438353 Bertin J (1983) Semiology of graphics: diagrams. Networks, Maps 10(00690805.1987), 10438353
66.
Zurück zum Zitat Gaertler M, Wagner D (2005) A hybrid model for drawing dynamic and evolving graphs. In: International symposium on graph drawing. Springer, Berlin, Heidelberg, pp 189–200 Gaertler M, Wagner D (2005) A hybrid model for drawing dynamic and evolving graphs. In: International symposium on graph drawing. Springer, Berlin, Heidelberg, pp 189–200
67.
Zurück zum Zitat MacEachren AM, Kraak MJ (2001) Research challenges in geovisualization. Cartogr Geogr Inf Sci 28(1):3–12CrossRef MacEachren AM, Kraak MJ (2001) Research challenges in geovisualization. Cartogr Geogr Inf Sci 28(1):3–12CrossRef
68.
Zurück zum Zitat Kietzmann JH, Hermkens K, McCarthy IP, Silvestre BS (2011) Social media? Get serious! Understanding the functional building blocks of social media. Bus Horiz 54(3):241–251CrossRef Kietzmann JH, Hermkens K, McCarthy IP, Silvestre BS (2011) Social media? Get serious! Understanding the functional building blocks of social media. Bus Horiz 54(3):241–251CrossRef
69.
Zurück zum Zitat Hanna R, Rohm A, Crittenden VL (2011) We’re all connected: the power of the social media ecosystem. Bus Horiz 54(3):265–273CrossRef Hanna R, Rohm A, Crittenden VL (2011) We’re all connected: the power of the social media ecosystem. Bus Horiz 54(3):265–273CrossRef
70.
Zurück zum Zitat Ahn JW, Taieb-Maimon M, Sopan A, Plaisant C, Shneiderman B (2011) Temporal visualization of social network dynamics: prototypes for nation of neighbors. In: International conference on social computing, behavioral-cultural modeling, and prediction. Springer, Berlin, Heidelberg, pp 309–316 Ahn JW, Taieb-Maimon M, Sopan A, Plaisant C, Shneiderman B (2011) Temporal visualization of social network dynamics: prototypes for nation of neighbors. In: International conference on social computing, behavioral-cultural modeling, and prediction. Springer, Berlin, Heidelberg, pp 309–316
71.
Zurück zum Zitat De Chiara D, Del Fatto V, Sebillo M, Tortora G, Vitiello G (2012) Tag@ map: a web-based application for visually analyzing geographic information through georeferenced tag clouds. In: International symposium on web and wireless geographical information systems. Springer, Berlin, Heidelberg, pp 72–81 De Chiara D, Del Fatto V, Sebillo M, Tortora G, Vitiello G (2012) Tag@ map: a web-based application for visually analyzing geographic information through georeferenced tag clouds. In: International symposium on web and wireless geographical information systems. Springer, Berlin, Heidelberg, pp 72–81
72.
Zurück zum Zitat Xiang Z, Du Q, Ma Y, Fan W (2017) A comparative analysis of major online review platforms: implications for social media analytics in hospitality and tourism. Tour Manag 58:51–65CrossRef Xiang Z, Du Q, Ma Y, Fan W (2017) A comparative analysis of major online review platforms: implications for social media analytics in hospitality and tourism. Tour Manag 58:51–65CrossRef
73.
Zurück zum Zitat Zhang Y, Cole ST (2016) Dimensions of lodging guest satisfaction among guests with mobility challenges: a mixed-method analysis of web-based texts. Tour Manag 53:13–27CrossRef Zhang Y, Cole ST (2016) Dimensions of lodging guest satisfaction among guests with mobility challenges: a mixed-method analysis of web-based texts. Tour Manag 53:13–27CrossRef
74.
Zurück zum Zitat Miah SJ, Vu HQ, Gammack J, McGrath M (2017) A big data analytics method for tourist behaviour analysis. Inf Manag 54(6):771–785CrossRef Miah SJ, Vu HQ, Gammack J, McGrath M (2017) A big data analytics method for tourist behaviour analysis. Inf Manag 54(6):771–785CrossRef
75.
Zurück zum Zitat Oender I (2017) Classifying multi-destination trips in Austria with big data. Tour Manag Perspect 21:54–58CrossRef Oender I (2017) Classifying multi-destination trips in Austria with big data. Tour Manag Perspect 21:54–58CrossRef
76.
Zurück zum Zitat Birenboim A, Reinau KH, Shoval N, Harder H (2015) High-resolution measurement and analysis of visitor experiences in time and space: the case of Aalborg zoo in Denmark. The Prof Geogr 67(4):620–629CrossRef Birenboim A, Reinau KH, Shoval N, Harder H (2015) High-resolution measurement and analysis of visitor experiences in time and space: the case of Aalborg zoo in Denmark. The Prof Geogr 67(4):620–629CrossRef
77.
Zurück zum Zitat Orellana D, Bregt AK, Ligtenberg A, Wachowicz M (2012) Exploring visitor movement patterns in natural recreational areas. Tour Manag 33(3):672–682CrossRef Orellana D, Bregt AK, Ligtenberg A, Wachowicz M (2012) Exploring visitor movement patterns in natural recreational areas. Tour Manag 33(3):672–682CrossRef
78.
Zurück zum Zitat Shoval N, McKercher B, Ng E, Birenboim A (2011) Hotel location and tourist activity in cities. Ann Tour Res 38(4):1594–1612CrossRef Shoval N, McKercher B, Ng E, Birenboim A (2011) Hotel location and tourist activity in cities. Ann Tour Res 38(4):1594–1612CrossRef
79.
Zurück zum Zitat Zheng Y (2015) Trajectory data mining: an overview. ACM Trans Intell Syst Technol (TIST) 6(3):29 Zheng Y (2015) Trajectory data mining: an overview. ACM Trans Intell Syst Technol (TIST) 6(3):29
81.
Zurück zum Zitat Alfred R, Leong LC, On CK, Anthony P (2014) A literature review and discussion of Malay rule—based Affix elimination algorithms. In: Uden L, Wang L, Corchado Rodríguez J, Yang HC, Ting IH (eds) The 8th international conference on knowledge management in organizations. Springer proceedings in complexity. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7287-8_23 Alfred R, Leong LC, On CK, Anthony P (2014) A literature review and discussion of Malay rule—based Affix elimination algorithms. In: Uden L, Wang L, Corchado Rodríguez J, Yang HC, Ting IH (eds) The 8th international conference on knowledge management in organizations. Springer proceedings in complexity. Springer, Dordrecht. https://​doi.​org/​10.​1007/​978-94-007-7287-8_​23
82.
Zurück zum Zitat Leong LC, Basri S, Alfred R (2012) Enhancing Malay stemming algorithm with background knowledge. In: Anthony P, Ishizuka M, Lukose D (eds) PRICAI 2012: trends in artificial intelligence. PRICAI 2012. Lecture Notes in Computer Science, vol 7458. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32695-0_68 Leong LC, Basri S, Alfred R (2012) Enhancing Malay stemming algorithm with background knowledge. In: Anthony P, Ishizuka M, Lukose D (eds) PRICAI 2012: trends in artificial intelligence. PRICAI 2012. Lecture Notes in Computer Science, vol 7458. Springer, Berlin, Heidelberg. https://​doi.​org/​10.​1007/​978-3-642-32695-0_​68
83.
Zurück zum Zitat Alfred R, Mujat A, Obit JH (2013) A ruled-based part of speech (RPOS) tagger for Malay text articles. In: Selamat A, Nguyen NT, Haron H (eds) Intelligent information and database systems. ACIIDS 2013. Lecture Notes in Computer Science, vol 7803. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36543-0_6 Alfred R, Mujat A, Obit JH (2013) A ruled-based part of speech (RPOS) tagger for Malay text articles. In: Selamat A, Nguyen NT, Haron H (eds) Intelligent information and database systems. ACIIDS 2013. Lecture Notes in Computer Science, vol 7803. Springer, Berlin, Heidelberg. https://​doi.​org/​10.​1007/​978-3-642-36543-0_​6
86.
Zurück zum Zitat Alfred R, Teoh RW (2019) Improving topical social media sentiment analysis by correcting unknown words automatically. In: Yap B, Mohamed A, Berry M (eds) Soft computing in data science. SCDS 2018. Communications in computer and information science, vol 937. Springer, Singapore. https://doi.org/10.1007/978-981-13-3441-2_23 Alfred R, Teoh RW (2019) Improving topical social media sentiment analysis by correcting unknown words automatically. In: Yap B, Mohamed A, Berry M (eds) Soft computing in data science. SCDS 2018. Communications in computer and information science, vol 937. Springer, Singapore. https://​doi.​org/​10.​1007/​978-981-13-3441-2_​23
87.
Zurück zum Zitat Marine-Roig E, Clavé SA (2015) Tourism analytics with massive user-generated content: a case study of Barcelona. J Destin Market Manag 4(3):162–172 Marine-Roig E, Clavé SA (2015) Tourism analytics with massive user-generated content: a case study of Barcelona. J Destin Market Manag 4(3):162–172
88.
Zurück zum Zitat Suhaimin MSM, Hijazi MHA, Alfred R, Coenen F (2017) Natural language processing based features for sarcasm detection: an investigation using bilingual social media texts. In: 2017 8th international conference on information technology (ICIT), Amman, pp 703–709. https://doi.org/10.1109/icitech.2017.8079931 Suhaimin MSM, Hijazi MHA, Alfred R, Coenen F (2017) Natural language processing based features for sarcasm detection: an investigation using bilingual social media texts. In: 2017 8th international conference on information technology (ICIT), Amman, pp 703–709. https://​doi.​org/​10.​1109/​icitech.​2017.​8079931
Metadaten
Titel
Modeling Tourism Using Spatial Analysis Based on Social Media Big Data: A Review
verfasst von
Zhu Chen
Rayner Alfred
Oliver Valentine Eboy
Copyright-Jahr
2021
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-33-4069-5_36