The user-generated content (UGC) published on the internet offers great advantages as a source of data. This study proposes a way to make better use of its potential to measure tourism destination image, based on the recommendations of Echtner and Ritchie. These authors indicate that in order to obtain a comprehensive picture of tourism destinations, it is necessary to carry out a holistic and attribute-based analysis using unstructured and structured data, respectively. Since UGC provides both types of data, here we propose its use to study and compare the images of five tourist cities. Our results demonstrate that UGC is a valid source for the study of tourism destination image, confirming the need to adopt a holistic and attribute-based approach to this concept. They also show that not all attributes influence the overall impression of a destination.
BourdieuP. (1979). The distinction: Social critique of judgment. Minuit.
4.
BrownG.SmithA.AssakerG. (2016). Revisiting the host city: An empirical examination of sport involvement, place attachment, event satisfaction and spectator intentions at the London Olympics. Tourism Management, 55(August), 160-172. https://doi.org/10.1016/j.tourman.2016.02.010
5.
CardonD. (2011). Internet Democracy: Promises and limits. Nouvelles Pratiques Sociales, 24(1), 159-163. https://doi.org/10.7202/1008225ar
6.
ChoiS.LehtoX. Y.MorrisonA. M. (2007). Destination image representation on the web: Content analysis of Macau travel related websites. Tourism Management, 28(1), 118-129. https://doi.org/10.1016/j.tourman.2006.03.002
7.
CracoliM. F.NijkampP. (2009). The attractiveness and competitiveness of tourist destinations: A study of Southern Italian regions. Tourism Management, 30(3), 336-344. https://doi.org/10.1016/j.tourman.2008.07.006
8.
CromptonJ. L. (1979). An assessment of the image of Mexico as a vacation destination and the influence of geographical location upon that image. Journal of Travel Research, 17(4), 18-24. https://doi.org/10.1177/004728757901700404
9.
DengN.LiuJ.DaiY.LiH. (2019). Different cultures, different photos: A comparison of Shanghai’s pictorial destination image between East and West. Tourism Management Perspectives, 30(April), 182-192. https://doi.org/10.1016/j.tmp.2019.02.016
10.
DoeyL.KurtaJ. (2011). Correspondence analysis applied to psychological research. Tutorials in Quantitative Methods for Psychology, 7(5), 5-14. https://doi.org/10.20982/tqmp.07.1.p005
11.
DolnicarS.GrünB. (2013). Validly measuring destination image in survey studies. Journal of Travel Research, 52(1), 3-14. https://doi.org/10.1177/0047287512457267
12.
DwivediM. (2009). Online destination image of India: A consumer based perspective. International Journal of Contemporary Hospitality Management, 21(2), 226-232. https://doi.org/10.1108/09596110910935714
13.
EchtnerC. M.RitchieJ. R. B. (1991). The meaning and measurement of destination image. Journal of Tourism Studies, 2(2), 2-12.
14.
EchtnerC. M.RitchieJ. R. B. (1993). The measurement of destination image: An empirical assessment. Journal of Travel Research, 31(4), 3-13. https://doi.org/10.1177/004728759303100402
EidR.El-KassrawyY. A.AgagG. (2019). Integrating destination attributes, political (in)stability, destination image, tourist satisfaction, and intention to recommend: A study of UAE. Journal of Hospitality & Tourism Research, 43(6), 839-866. https://doi.org/10.1177/1096348019837750
17.
ElliotS.PapadopoulosN. (2016). Of products and tourism destinations: An integrative, cross-national study of place image. Journal of Business Research, 69(3), 1157-1165. https://doi.org/10.1016/j.jbusres.2015.08.031
FormicaS.UysalM. (2006). Destination attractiveness based on supply and demand evaluations: An analytical framework. Journal of Travel Research, 44(4), 418-430. https://doi.org/10.1177/0047287506286714
20.
GallarzaM. G.SauraI. G.Garcı́aH. C. (2002). Destination image: Towards a conceptual framework. Annals of Tourism Research, 29(1), 56-78. https://doi.org/10.1016/S0160-7383(01)00031-7
21.
GoversR.GoF. M. (2003). Deconstructing destination image in the information age. Information Technology & Tourism, 6(1), 13-29. https://doi.org/10.3727/109830503108751199
22.
GreenacreM. (2007). Correspondence analysis in practice (2nd ed.). Chapman & Hall/CRC.
23.
GunnC. (1988). Vacationscapes: Desinging tourist regions. Van Nostrand Reinhold.
24.
HsuC. H. C.WolfeK.KangS. K. (2004). Image assessment for a destination with limited comparative advantages. Tourism Management, 25(1), 121-126. https://doi.org/10.1016/S0261-5177(03)00062-1
JohnsonP. A.SieberR. E.MagnienN.AriwiJ. (2012). Automated web harvesting to collect and analyse user-generated content for tourism. Current Issues in Tourism, 15(3), 293-299. https://doi.org/10.1080/13683500.2011.555528
28.
KirilenkoA. P.StepchenkovaS.KimH.LiX. R. (2018). Automated sentiment analysis in tourism: Comparison of approaches. Journal of Travel Research, 57(8), 1012-1025. https://doi.org/10.1177/0047287517729757
29.
KotrasB. (2020). Opinions that matter: The hybridization of opinion and reputation measurement in social media listening software. Media, Culture & Society, 42(7-8), 1495-1511. https://doi.org/10.1177/0163443720939427
30.
KozakM.NieldK. (1998). Importance-performance analysis and cultural perspectives in Romanian Black sea resorts. Anatolia, 9(2), 99-116. https://doi.org/10.1080/13032917.1998.9686964
31.
LaiK.LiY. (2012). Core-periphery structure of destination image: Concept, evidence and implication. Annals of Tourism Research, 39(3), 1359-1379. https://doi.org/10.1016/j.annals.2012.02.008
32.
LineN. D.CostenW. M. (2017). Nature-based tourism destinations: A dyadic approach. Journal of Hospitality & Tourism Research, 41(3), 278-300. https://doi.org/10.1177/1096348014538053
33.
LiuY.HuangK.BaoJ.ChenK. (2019). Listen to the voices from home: An analysis of Chinese tourists’ sentiments regarding Australian destinations. Tourism Management, 71(April), 337-347. https://doi.org/10.1016/j.tourman.2018.10.004
34.
LuW.StepchenkovaS. (2015). User-generated content as a research mode in tourism and hospitality applications: Topics, methods, and software, Journal of Hospitality Marketing & Management, 24(2), 119-154. https://doi.org/10.1080/19368623.2014.907758
Marine-RoigE. (2017). Measuring destination image through travel reviews in search engines. Sustainability, 9(8), Article 1425. https://doi.org/10.3390/su9081425
37.
Mayer-SchönbergerV.CukierK. (2013). Big data: A revolution that will transform how we live, work, and think. Houghton Mifflin Harcourt.
38.
MurphyL. (2000). Australia’s image as a holiday destination-perceptions of backpacker visitors. Journal of Travel & Tourism Marketing, 8(3), 21-45. https://doi.org/10.1300/J073v08n03_02
39.
MurphyP.PritchardM. P.SmithB. (2000). The destination product and its impact on traveller perceptions. Tourism Management, 21(1), 43-52. https://doi.org/10.1016/S0261-5177(99)00080-1
ÖzgenH. K. S.KozakM. (2015). Social media practices applied by city hotels: A comparative case study from Turkey. Worldwide Hospitality and Tourism Themes, 7(3), 229-241. https://doi.org/10.1108/WHATT-03-2015-0010
PanB.MacLaurinT.CrottsJ. C. (2007). Travel blogs and the implications for destination marketing. Journal of Travel Research, 46(1), 35-45. https://doi.org/10.1177/0047287507302378
RodriguesA. I.CorreiaA.KozakM. (2017). Assessing lake-destination image: Insights from the industry side. International Journal of Culture, Tourism and Hospitality Research, 11(1), 5-17. https://doi.org/10.1108/IJCTHR-09-2015-0116
46.
Rojas-de-GraciaM. M.Casado-MolinaA. M.Alarcón-UrbistondoP. (2021). Relationship between reputational aspects of companies and their share price in the online environment. Technology in Society, 64(February), 101500. https://doi.org/10.1016/j.techsoc.2020.101500
47.
Rojas-MéndezJ. I.HineM. J. (2017). Countries’ positioning on personality traits. Journal of Vacation Marketing, 23(3), 233-247. https://doi.org/10.1177/1356766716649227
48.
SahinS.BalogluS. (2011). Brand personality and destination image of Istanbul. Anatolia: An International Journal of Tourism and Hospitality Research, 22(1), 69-88. https://doi.org/10.1080/13032917.2011.556222
49.
SernaA.MarchioriE.GerrikagoitiaJ. K.Alzua-SorzabalA.CantoniL. (2015). An auto-coding process for testing the cognitive-affective and conative model of destination image. In TussyadiahI.InversiniA. (Eds.), Information and communication technologies in tourism 2015 (pp. 111-123). Springer. https://doi.org/10.1007/978-3-319-14343-9_9
SinaeepourfardA.KrogstieJ.PetersenS. A.GustavsenA. (2018). A zero emission neighbourhoods data management architecture for smart city scenarios: Discussions toward 6Vs challenges. In 2018 International Conference on Information and Communication Technology Convergence (ICTC) (pp. 658-663). IEEE. https://doi.org/10.1109/ICTC.2018.8539669
StepchenkovaS.LiX. R. (2014). Destination image: Do top-of-mind associations say it all?Annals of Tourism Research, 45(March), 46-62. https://doi.org/10.1016/j.annals.2013.12.004
55.
TanW.-K.WuC.-E. (2016). An investigation of the relationships among destination familiarity, destination image and future visit intention. Journal of Destination Marketing & Management, 5(3), 214-226. https://doi.org/10.1016/j.jdmm.2015.12.008
56.
TasciA. D. A.GartnerW. C. (2007). Destination image and its functional relationships. Journal of Travel Research, 45(4), 413-425. https://doi.org/10.1177/0047287507299569
57.
TasciA. D. A.GartnerW. C.CavusgilS. T. (2007). Conceptualization and operationalization of destination image. Journal of Hospitality & Tourism Research, 31(2), 194-223. https://doi.org/10.1177/1096348006297290
58.
ToralS. L.Martínez-TorresM. R.Gonzalez-RodriguezM. R. (2018). Identification of the unique attributes of tourist destinations from online reviews. Journal of Travel Research, 57(7), 908-919. https://doi.org/10.1177/0047287517724918
59.
TsaiC. F.ChenK.HuY. H.ChenW. K. (2020). Improving text summarization of online hotel reviews with review helpfulness and sentiment. Tourism Management, 80(October), 104122. https://doi.org/10.1016/j.tourman.2020.104122
60.
WangY.LiX. R.LaiK. (2017). A meeting of the minds: Exploring the core–periphery structure and retrieval paths of destination image using social network analysis. Journal of Travel Research, 57(5), 612-626. https://doi.org/10.1177/0047287517706262
