Exploring User-Generated Content for Improving Destination Knowledge: The Case of Two World Heritage Cities

被引：11

作者：

Antonio, Nuno ^{[1
,2
]}

Correia, Marisol B. ^{[2
,3
,4
,5
]}

Ribeiro, Filipa Perdigao ^{[2
,3
]}

机构：

[1] Univ Nova Lisboa, Nova Informat Management Sch NOVA IMS, Campus Campolide, P-1070312 Lisbon, Portugal

[2] Ctr Tourism Res Dev & Innovat CiTUR, Campus Penha, Faro, Portugal

[3] Univ Algarve, Sch Management Hospitality & Tourism ESGHT, Campus Penha, P-8005139 Faro, Portugal

[4] Res Ctr Tourism Sustainabil & Well Being CinTurs, Campus Gambelas, P-8005139 Faro, Portugal

[5] Univ Lisbon, Inst Super Tecn, CEG IST, P-1049001 Lisbon, Portugal

来源：

SUSTAINABILITY | 2020年 / 12卷 / 22期

关键词：

user-generated content; data science; text mining; sentiment analysis; eWOM; UNESCO heritage sites; TOURISM; PERFORMANCE; REVIEWS; DESIGN; IMPACT;

D O I：

10.3390/su12229654

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

This study explores two World Heritage Sites (WHS) as tourism destinations by applying several uncommon techniques in these settings: Smart Tourism Analytics, namely Text mining, Sentiment Analysis, and Market Basket Analysis, to highlight patterns according to attraction, nationality, and repeated visits. Salamanca (Spain) and Coimbra (Portugal) are analyzed and compared based on 8,638 online travel reviews (OTR), from TripAdvisor (2017-2018). Findings show that WHS reputation does not seem to be relevant to visitors-reviewers. Additionally, keyword extraction reveals that the reviews do not differ from language to language or from city to city, and it was also possible to identify several keywords related to history and heritage; in particular, architectural styles, names of kings, and places. The study identifies topics that could be used by destination management organizations to promote these cities, highlights the advantages of applying a data science approach, and confirms the rich information value of OTRs as a tool to (re)position the destination according to smart tourism design tenets.

引用

页码：1 / 19

页数：19

共 76 条

[1]

Adedoyin-Olowe M., 2013, A survey of data mining techniques for social media analysis

[2]

Adie BA, 2017, J HERIT TOUR, V12, P67, DOI 10.1080/1743873X.2016.1151429

[3]

Agrawal R., 1994, P VLDB ENDOWMENT, P487

[4]

Amstrong G., 2014, PRINCIPLES MARKETING, V15th

[5]

[Anonymous], 2015, CULTURAL TOURISM PAR

[6]

[Anonymous], **DATA OBJECT**

[7]

[Anonymous], 2019, ESTADISTICA MOVIMIEN

[8]

[Anonymous], 2011, DIGITAL CULTURE E TO

[9]

[Anonymous], **DATA OBJECT**

[10]

[Anonymous], 2012, Mining text data, DOI DOI 10.1007/978-1-4614-3223-4_13

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