Presentation done by Estela Mariné-Roig, during ENTER2015 PhD Workshop.

1. ENTER 2015 PhD Workshop Slide Number 1
From the projected to the transmitted image:
The 2.0 construction of tourist destination
image and identity in Catalonia
Estela Mariné-Roig
DOCTORAL THESIS
Supervised by Prof. Dr. Salvador Anton Clavé
University Rovira i Virgili, Catalonia, Spain
estela.marine@urv.cat
http://www.urv.cat

2. ENTER 2015 PhD Workshop Slide Number 2
Content
1. Aims and hypotheses
2. Theoretical framework
3. Methodology
4. Selected results
5. Concluding remarks

3. ENTER 2015 PhD Workshop Slide Number 3
1. Aims
 Explore online projected and perceived images of a destination
and assess their correspondence.
 Shed light on the role of online user-generated image in the
destination image formation process by building an explanatory
theoretical-conceptual model.
General
Specific
 Provide a useful methodology for studies concerning online
image and identity.
 Give insight into the specific case of Catalonia and provide an
understanding of the online image identity of a destination.

4. ENTER 2015 PhD Workshop Slide Number 4
1. Hypotheses
 H1. The perceived image that tourists hold once they have
visited a destination does not correspond to the one
constructed and projected by the destination (neither in terms
of general represented place identity, nor in terms of cultural
identity).
H2. With the creation of user-generated content and its
transmission through the social media, image perceived by
tourists becomes transmitted image and the image formation
circle is increasingly closed from tourist to tourist due to its
great potential influence. The user-generated image online
(such as in travel blogs and reviews) has a greater capacity or
potential to influence than the official destination image (such
as in official tourism websites).

5. ENTER 2015 PhD Workshop Slide Number 5
2. Background:
Destination image
Tourist image is the total sum of ideas, feelings, values,
impressions, attributes and identities attached to a
place, within both the perceived image by tourists and
the representations projected by different actors, which
are transmitted in certain contexts and through certain
communication channels
(Derived from Gartner, 1993; Gallarza et al., 2002; Kim & Richardson,
2003; Mercille, 2005; Almeida & Buzinde, 2007; Anton & González,
2008, among others).

6. ENTER 2015 PhD Workshop Slide Number 6
2. Background: Online image
 Intentionality and power struggles in image projection with
Web 2.0
 Users have a social and leisure motivation to post tourist contents online
(Cox et al.,2008;Casaló, 2009; Clever et al. 2009; Bosangit & Mena, 2009).
 The power of the different agents on the Internet seems to become
diluted  empowerment of users in detriment of tourism organizations
(Akehurst, 2008).
 Representative dissonance and image congruency issue
 Perceived tourist image becomes projected through user
generated content  sharing experience (González, 2010).
 Travel blogs and reviews
 Official tourism websites
Online
image
Specially interesting to study
perceived-transmitted image of
tourists  Objects for projected
and perceived travel research.
Representatives of the
destinations.

7. ENTER 2015 PhD Workshop Slide Number 7
Catalonia
 First order world tourism destination.
Second top tourist region in EU-27.
 2013: 15.6 million foreign tourists.
 Barcelona is among the top European
tourist capitals.
 9 regional tourist brands.
3. Methodology: Case study

8. ENTER 2015 PhD Workshop Slide Number 8
 Process for obtaining a suitable database for analysis:
1. Data sources
2. Data collection
3. Data download
4. Data arrangement
5. Data cleaning
6. Data debug
7. Data language detection
8. Data mining
9. Data dissemination
 Travel blogs and reviews
 Official tourism websites
3. Methodology: Database

9. ENTER 2015 PhD Workshop Slide Number 9
3. Methodology: Database
 Process for obtaining a suitable database for analysis:
1. Data sources
2. Data collection
3. Data download
4. Data arrangement
5. Data cleaning
6. Data debug
7. Data language detection
8. Data mining
9. Data dissemination

10. ENTER 2015 PhD Workshop Slide Number 10
 Process for obtaining a suitable database for analysis:
1. Data sources
2. Data collection
3. Data download
4. Data arrangement
5. Data cleaning
6. Data debug
7. Data language detection
8. Data mining
9. Data dissemination
Correct noun Misspellings
Barcelona Bathelona, Barcellona, Barthelonaaaa, Bar-th-elona, Bar-tha-lona, Bar-the-lona ...
Casa Batlló Batllo House; Casa Batillo, Batilló, Batlla, Batllao, Batllò, Bátllo, Batlo, Battllo, Battló ...
Antoni Gaudí Antonio Gaudi; Gaudì, Gaüdi, Gaudie, Gaudii, Goudi, Goudí, Guadi, Gualdi, Gudi ...
Barri Gòtic Barri Gotico; Bari Gotic; Ghotic Barrio, District, Quarter; Gotic area, neighborhood ...
Parc Güell Parc Guël, Güel, Guéll, Guelle; Park Gueil, Guel, Güelle, Guelli; Parque Guelle, Güelle ...
Montjuïc Monjuic, Montjeuic, Montjic, Montjouïc, Montjuîc, Montjuich, Montjuiic, Montjuik ...
 Visibility
 Usage
 Size
3. Methodology: Database

11. ENTER 2015 PhD Workshop Slide Number 11
Pyrenees Val d’Aran Terres de Lleida Catalunya Central Costa Brava
Costa Barcelona Barcelona Costa Daurada Terres de l’Ebre Whole Catalonia
Domain (particular acronym) Brand (particular acronym)
HTML
en
PDF
en
PDF
en + other
BarcelonaTurisme.com (BT) Barcelona (Barna) 258 12 3
CostaBrava.org (CB) Costa Brava (cBrav) 1,012 8 -
CostaDaurada.info (CD) Costa Daurada (cDaur) 51 6 7
GenCat.cat (GC) Catalonia (unClass) 10 21 -
GenCat.cat/turistex_nou (GC) Catalonia (unClass) 48 29 1
LleidaTur.com (LT) Terres de Lleida (tLlei) 173 12 2
Spain.info (SP) Catalonia (unClass) 981 5 -
TerresDelEbre.org (TE) Terres de l’Ebre (tEbre) 82 7 1
TurismeDeCatalunya.com (TC) Catalonia (unClass) 250 1 -
TurismePropBarcelona.cat (PB)
Costa Barcelona (cBarc)
Catalunya Central (CatCe)
55 - 27
VisitPirineus.com (VP) Pirineus (Pyren) 28 2 -
VisitValdAran.com (VV) Val d’Aran (vAran) 73 - 6
3. Methodology: Database
Official
Tourism
Websites

12. ENTER 2015 PhD Workshop Slide Number 12
Domain Barcelona Other towns Unclassified Empty First blog
GetJealous.com (GJ) 0 0 1,164 * 371 2001-08-27
MyTripJournal.com (MT) 536 72 0 - 2001-07-25
RealTravel.com (RT) 409 69 0 - 1984-07-31
TravBuddy.com (TY) 832 60 0 ** 11 1985-05-20
TravelBlog.org (TB) 2,348 280 106 - 1997-03-07
TravellersPoint.com (TS) 0 0 596 - 1986-05-09
TravelPod.com (TP) 998 481 0 - 1984-12-27
TripAdvisor.com (TA) 67,882 34,519 43 *** 112,698 2002-10-17
VirtualTourist.com (VT) 10,289 2,192 285 *** 515 1999-12-08
 Travel blogs and reviews per tourism brands
Web
au ca de es fr ie il It nl+be nz uk us
RT 36 32 4 8 3 2 0 2 4 5 23 103
TY 26 36 8 26 5 10 4 7 62 5 46 209
TP 149 100 14 38 11 10 2 10 4 23 70 315
TS 54 21 2 6 1 2 1 1 2 11 25 61
TA 191 275 39 217 53 272 59 43 96 29 1,587 2,049
VT 32 29 27 142 19 22 15 32 87 8 234 286
 Travel blog and review database
 Country of origin  Language of posts
3. Methodology: Database
Travel blogs & Reviews

13. ENTER 2015 PhD Workshop Slide Number 13
Indexed pagesVisibility Presence in the social media Link-based ranks
Usage Geographical distribution of users Visit-based ranks
Domain (particular acronym) Google
GetJealous.com (GJ) 716,000
MyTripJournal.com (MT) 921,000
RealTravel.com (RT) 2,630,000
TravBuddy.com (TY) 282,000
TravelBlog.org (TB) 8,860,000
TravellersPoint.com (TS) 1,380,000
TravelPod.com (TP) 11,400,000
TripAdvisor.com (TA) 116,000,000
VirtualTourist.com (VT) 7,910,000
Domain (particular acronym) Google
BarcelonaTurisme.com (BT) 27,400
CostaBrava.org (CB) 116,000
CostaDaurada.info (CD) 439
GenCat.cat (GC) 8,210,000
LleidaTur.com (LT) 23,000
Spain.info (SP) 1,510,000
TerresDelEbre.org (TE) 33,400
TurismePropBarcelona.cat (PB) 109,000
VisitPirineus.com (VP) 58,000
VisitValdAran.com (VV) 115,000
Official Tourism Websites Travel Blog & Review Websites
Travel Blog and Review websites have a greater visibility than Official
Tourism websites
Travel blogs and reviews audience
Travel Blog and Review websites have a wider usage than Official
Tourism websites
Official Tourism Websites
Mainly from Spain
3. Methodology: Database
Data dissemination

14. ENTER 2015 PhD Workshop Slide Number 14
CONCEPT DECISION
Receptacle  Text
Approach  Quantitative approach  massive analysis
Interpretation  Thematic approach
Categories of
analysis
 Geography: region and sub-regions
 Attraction factors
 Feelings and dichotomies
 Cultural identity references
Analysis units  Keywords within categories
Measuring system  Frequency counts
Software  Site Content Analyzer
 Other software: Java utility to process strings
3. Methodology:Content analysis

15. ENTER 2015 PhD Workshop Slide Number 15
 Word groups (total databases)
 Matrix with content categories (file-per-file)
 Statistics
 Additional measures
Descriptive statistics
P-correlation
1st level
 Most frequent words (50 meaningful words)
 Specific preliminary study of outstanding elements (Gaudí)
 User-generated image per brands
 Spatial indexes
2nd level
3rd level
Group of
categories
Territory1 Territory 2 Territory 3 Territory 4 …
Category 1 SW Density ‰ … … … …
Subcategory 1a … … … … …
Subcategory 1b … … … … …
Category 2 … … … … …
Subcategory 2a … … … … …
Subcategory 2b … … … … …
Subcategory 2c … … … … …
… … … … … …
Location quotient:
..
.
. x
x
x
x
LQ i
j
ij
ij  Localization coefficient: 

h
j
j
i
ij
i
x
x
x
x
LC
1 ..
.
.2
1
Specialization coefficient: 

n
i
i
j
ij
j
x
x
x
x
SC
1 ..
.
.2
1
Diversification coefficient:




 n
i ij
n
i ij
j
xn
x
DC
1
2
1
2
)(
1
n: Number of sectors
.ix : Total value in sector i
ijx : Value in sector i in region j
h: Number of regions
jx. : Total value in region j
..x : Total value (in all sectors and regions)
Confirmatory cluster analysis
Zoom into a subject through
“regular language”
Group or
category
Count Site-Wide Density Average Weight
Word_a1 ... ... ...
Word_a2 ... ... ...
Word_a3 ... ... ...
Word_a4 ... ... ...
GROUP A ... ... ...
Word_b1 ... ... ...
Word_b2 ... ... ...
GROUP B ... ... ...
CATEGORY 1 CATEGORY 2 CATEGORY 3 CATEGORY 4
T-BLOG 1 XXX XXX XXX XXX
T-BLOG 2 XXX XXX XXX XXX
T-BLOG 3 XXX XXX XXX XXX
T-BLOG 4 XXX XXX XXX XXX
… … … … …
3. Methodology:Measures

16. ENTER 2015 PhD Workshop Slide Number 16
OFFICIAL TOURISM WEBSITES TRAVEL BLOGS AND REVIEWS
Rank Word Count
Site-wide
Density
Average
Weight
Rank Word Count
Site-wide
Density
Average
Weight
1 Barcelona 8105 0.69% 9.31 1 Barcelona 100248 3.36% 40.02
2 Catalonia 5628 0.48% 11.59 2 Sagrada Família 18,859 0.62% 38.65
3 route 4904 0.42% 11.05 3 city 17372 0.58% 9.78
4 area 3665 0.31% 4.37 4 Gaudí 16777 0.56% 17.80
5 tourist 3629 0.31% 11.65 5 great 13222 0.44% 10.85
6 museum 3516 0.30% 12.48 6 Parc Güell 12482 0.40% 40.27
7 Girona 3344 0.28% 15.96 7 people 11706 0.39% 4.30
8 town 3071 0.26% 4.57 8 night 10941 0.36% 7.20
9 Catalan 3055 0.26% 2.74 9 way 10800 0.36% 6.62
10 centre 2950 0.25% 4.90 10 tour 10673 0.35% 9.61
11 century 2924 0.25% 2.08 11 Spain 10540 0.35% 19.72
12 turisme 2893 0.25% 14.91 12 good 10231 0.34% 5.56
13 church 2793 0.24% 5.82 13 place 9941 0.33% 5.98
14 city 2742 0.23% 3.60 14 Spanish 8802 0.29% 9.06
15 museu 2702 0.23% 7.75 15 bus 8729 0.29% 10.66
3,171 OTWs pages
27,104 T-B&R entries
1st level
Top words
Mentions of
brands and
municipalities
(Site-wide density)
4. Selected results

17. ENTER 2015 PhD Workshop Slide Number 17
Attraction factors
Official tourism websites Travel blogs and reviews
Count Density Weight Count Density Weight
1. Food and Wine 13,715 14.18‰ 7.30 38,167 13.67‰ 7.23
1.1 Food and Drinks 10,554 10.92‰ 7.45 33,162 11.88‰ 6.80
1.2 Wine 3,161 3.27‰ 6.85 5,005 1.79‰ 10.11
2. Intangible heritage 2,226 2.30‰ 6.29 6,303 2.26‰ 14.98
3. Leisure and Recreation 11,408 11.80‰ 10.25 37,133 13.30‰ 15.26
3.1 Nightlife & partying 2,424 2.51‰ 6.04 18,667 6.69‰ 12.19
3.2 Theme Parks 550 0.57‰ 10.36 4,366 1.56‰ 34.37
3.3 Wellness 2,126 2.20‰ 6.87 3,851 1.38‰ 15.54
3.4 Theatre/spectacle/cinema 5,528 5.72‰ 14.11 9,258 3.32‰ 12.76
3.5 Leisure remaining words 780 0.81‰ 5.06 991 0.35‰ 11.24
4. Nature and active tourism 27,402 28.34‰ 6.37 15,847 5.68‰ 11.34
4.1 Nature elements and places 16,945 17.53‰ 6.28 10,133 3.63‰ 12.08
4.2 Nature sports/ active tourism 3,069 3.17‰ 7.78 2,673 0.95‰ 11.60
4.3 Rural landscape 1,916 1.98‰ 6.92 580 0.21‰ 6.55
4.4 Nature remaining words 5,472 5.66‰ 5.58 2,461 0.88‰ 9.63
5. Sports 6,082 6.29‰ 7.54 15,264 5.47‰ 17.82
5.1 FC Barcelona 118 0.12‰ 9.41 4,362 1.56‰ 27.51
5.2 Sporting events/watching 999 1.03‰ 4.06 9,523 3.41‰ 13.52
5.3 Other sports 4,965 5.14‰ 8.44 1,125 0.40‰ 15.18
6. Sun, Sea, Sand + nautical 18,667 19.31‰ 13.77 32,406 11.61‰ 12.41
7. Tangible Heritage 69,133 71.50‰ 7.69 175,669 62.92‰ 22.33
7.1 Buildings and architecture 10,177 10.53‰ 3.58 29,412 10.54‰ 13.75
7.2 Gaudí 2,025 2.09‰ 8.33 54,648 19.57‰ 32.19
7.3 Artists 3,920 4.05‰ 7.26 9,190 3.29‰ 23.72
7.4 Art, design, art styles 13,436 13.90‰ 5.40 17,523 6.28‰ 13.04
7.5 Museums 7,095 7.34‰ 12.26 12,264 4.39‰ 25.65
7.6 Archaeological sites 2,453 2.54‰ 9.76 3,167 1.13‰ 13.41
7.7 History/industrial 6,568 6.79‰ 8.27 5,037 1.80‰ 7.19
7.8 Military/castles 5,140 5.32‰ 8.57 9,202 3.30‰ 19.66
7.9 Monuments/sculptures 1,768 1.83‰ 9.78 8,108 2.90‰ 19.32
7.10 Religious heritage 11,345 11.73‰ 7.05 24,497 8.77‰ 22.75
7.11 Culture remaining words 5,206 5.38‰ 13.60 2,621 0.94‰ 9.14
8. Urban environment 13,523 13.99‰ 6.90 74,675 26.75‰ 17.34
8.1 Shopping 1,628 1.68‰ 4.86 12,230 4.38‰ 8.15
8.2 Barcelona attractions 2,812 2.91‰ 7.60 30,685 10.99‰ 23.66
8.3 Other city attractions 316 0.33‰ 3.01 612 0.22‰ 22.58
8.4 Urban tourism/general sites 8,767 9.07‰ 7.20 31,148 11.16‰ 14.62
3,124 OTWs pages
25,357 T-B&R entries
2nd level
4. Selected results
Attraction factors

18. ENTER 2015 PhD Workshop Slide Number 18
3,124 OTWs pages
25,357 T-B&R entries
2nd level
Official tourism websites Travel blogs and reviews
1. Old/Old-fashioned 1. Beautiful
2. Beautiful 2. Fun/Interesting
3. Fun/Interesting 3. Old/Old-fashioned
4. New/Fashionable 4. Love
5. Authentic 5. New/Fashionable
6. Quiet 6. Authentic
7. Lively 7. Full
8. Pleasant 8. Relax
9. Love 9. Cheap
10. Relax 10. Noisy
Attraction factor
Official tourism websites Travel blogs and reviews
Count Density Weight Count Density Weight
1 Good feelings 11,144 11.53‰ 3.05 105,519 37.80‰ 8.52
2 Bad feelings 807 0.83‰ 2.59 21,591 7.73‰ 5.14
3 Love 573 0.59‰ 3.09 6,973 2.50‰ 7.15
4 Hate 7 0.01‰ 0.00 484 0.17‰ 4.98
5 Beautiful 3,754 3.88‰ 2.94 16,799 6.02‰ 9.93
6 Ugly 6 0.01‰ 0.00 341 0.12‰ 5.25
7 Pleasant 632 0.65‰ 3.40 2,389 0.86‰ 5.44
8 Unpleasant 8 0.01‰ 0.00 310 0.11‰ 5.55
9 Friendly 99 0.10‰ 2.22 1,434 0.51‰ 4.15
10 Unfriendly 2 0.00‰ 0.00 34 0.01‰ 8.82
11 Fun/interesting 2,966 3.07‰ 4.10 15,885 5.69‰ 7.58
12 Boring 33 0.03‰ 0.00 1,077 0.39‰ 3.51
13 Lively 663 0.69‰ 5.58 1,675 0.60‰ 6.57
14 Gloomy 89 0.09‰ 11.24 469 0.17‰ 2.75
15 Noisy 162 0.17‰ 0.93 2,467 0.88‰ 4.01
16 Quiet 812 0.84‰ 1.65 1,835 0.66‰ 5.39
17 Full 236 0.24‰ 0.30 4,637 1.66‰ 5.12
18 Empty 31 0.03‰ 0.00 626 0.22‰ 4.92
19 Orderly 241 0.25‰ 0.12 1,178 0.42‰ 3.07
20 Chaotic 101 0.10‰ 7.23 805 0.29‰ 6.86
21 Clean 164 0.17‰ 0.92 1,161 0.42‰ 5.00
22 Dirty 84 0.09‰ 0.24 1,060 0.38‰ 8.93
23 Relax 508 0.53‰ 1.30 3,943 1.41‰ 4.41
24 Distress 55 0.06‰ 0.36 343 0.12‰ 2.19
25 Authentic 1,619 1.67‰ 2.84 5,703 2.04‰ 6.55
26 Inauthentic 15 0.02‰ 0.67 647 0.23‰ 8.51
27 New/Fashionable 2,296 2.37‰ 1.74 5,771 2.07‰ 7.79
28 Old/old-fashioned 4,016 4.15‰ 5.48 8,059 2.89‰ 8.57
29 Cheap 35 0.04‰ 0.00 2,485 0.89‰ 4.40
30 Expensive 80 0.08‰ 5.62 2,043 0.73‰ 6.74
31 Modest/poor 480 0.50‰ 3.73 1,569 0.56‰ 4.47
32 Luxurious/wealthy 418 0.43‰ 1.89 759 0.27‰ 6.19
33 Safe 414 0.43‰ 6.55 779 0.28‰ 3.90
34 Unsafe 75 0.08‰ 5.87 2,150 0.77‰ 7.38
Top attributes
Feelings & dichotomies
4. Selected results

19. ENTER 2015 PhD Workshop Slide Number 19
3,124 OTWs pages
25,357 T-B&R entries
2nd level
OfficialTourism
Websites
Travel blogs and reviews
Attraction factor
Official tourism websites Travel blogs and reviews
Count Density Weight Count Density Weight
Festa Major 124 0.13‰ 20.32 355 0.13‰ 24.03
Rural/Farming festivities 45 0.05‰ 10.89 26 0.01‰ 31.15
Aplec 44 0.05‰ 14.77 0 0.00‰ 0.00
Patum 57 0.06‰ 0.35 2 0.00‰ 70.00
Fira del teatre 4 0.00‰ 10.00 0 0.00‰ 0.00
Tarraco viva 4 0.00‰ 0.00 2 0.00‰ 0.00
Religious traditions 293 0.30‰ 7.41 780 0.28‰ 17.30
Sant Joan 30 0.03‰ 11.00 34 0.01‰ 21.18
Sant Jordi 181 0.19‰ 11.21 178 0.06‰ 24.27
Castanyada 13 0.01‰ 10.00 4 0.00‰ 40.00
Saint Valentine 1 0.00‰ 0.00 12 0.00‰ 0.00
Halloween 2 0.00‰ 0.00 126 0.05‰ 11.51
Carnival 305 0.32‰ 8.00 1,209 0.43‰ 10.33
Feria de abril 0 0.00‰ 0.00 8 0.00‰ 25.00
Castellers 167 0.17‰ 0.90 445 0.16‰ 21.12
Correbou 4 0.00‰ 0.00 1 0.00‰ 0.00
Giants and Dwarfs 90 0.09‰ 1.33 223 0.08‰ 17.31
Correfoc 37 0.04‰ 1.89 139 0.05‰ 17.77
Fireworks 71 0.07‰ 2.54 466 0.17‰ 5.47
Siesta 1 0.00‰ 0.00 650 0.23‰ 5.52
Bullfighting 19 0.02‰ 2.11 918 0.33‰ 16.66
Sardana 78 0.08‰ 10.38 244 0.09‰ 28.28
Catalan dances 9 0.01‰ 0.00 2 0.00‰ 0.00
Accordionists 6 0.01‰ 0.00 0 0.00‰ 0.00
Flamenco 60 0.06‰ 3.66 1,637 0.59‰ 27.29
Spanish Guitar 20 0.02‰ 8.00 418 0.15‰ 4.95
Ballet 34 0.04‰ 0.00 31 0.01‰ 5.48
Belly dancing 0 0.00‰ 0.00 1 0.00‰ 0.00
Salsa 6 0.01‰ 1.67 247 0.09‰ 12.02
Cultural and geographical
identity reference
Cultural
identity
elements
Catalan Spanish Mediterranean European Global
Cultural Identity
4. Selected results

20. ENTER 2015 PhD Workshop Slide Number 20
3,124 OTWs pages
25,357 T-B&R entries
2nd level
Official Tourism Websites Travel Blogs and Reviews
Barna 1. New/fashionable (0.818)
2. Culture remaining words (0.784)
3. Cheap (0.756)
4. Catalan (0.747)
5. Urban environment (0.712)
6. History/industrial (0.696)
7. Authentic (0.696)
8. Leisure and recreational activities
(0.695)
9. Leisure remaining words (0.690)
10. shopping (0.673)
11. orderly (0.670)
12. Barcelona attractions (0.666)
1. Tangible Heritage (0.368)
2. Urban Environment (0.347)
3. Gaudí (0.316)
4. Spanish (0.315)
5. Buildings and architecture (0.303)
6. Good feelings (0.300)
7. Barcelona attractions (0.286)
8. Urban tourism/general sites
(0.280)
9. Bad feelings (0.253)
10. Food and Drinks (0.242)
11. Food and Wine (0.226)
12. Art, design, art styles (0.226)
Official Tourism Websites Travel Blogs and Reviews
cDaur 1. Other city attractions (0.546)
2. Good feelings (0.523)
3. Sun, Sea, Sand (0.518)
4. Theme Parks (0.516)
5. Archaeological sites (0.506)
6. Old/old-fashioned (0.503)
7. Leisure remaining words (0.501)
8. Catalan (0.501)
9. Leisure and recreational activities
(0.497)
10. Intangible Heritage (0.490)
11. History/industrial (0.488)
12. Tangible heritage (0.473)
1. Archaeological sites (0.284)
2. Other city attractions (0.138)
3. Tarraco viva (0.138)
4. Theme Parks (0.110)
5. Old/old-fashioned (0.100)
6. Mediterranean (0.090)
7. Sun, Sea, Sand (0.084)
8. tllei (0.077)
9. Intangible Heritage (0.074)
10. Art, design, art styles (0.073)
11. Leisure and recreational activities
(0.071)
12. History/industrial (0.069)
Barcelona
Costa Daurada
4. Selected results
Correlations brands/categories

21. ENTER 2015 PhD Workshop Slide Number 21
Attraction factor Barna
Most Freq.
Words
Comments
7. Tangible Heritage 46.88%
- Sagrada Família
- Gaudí
- Parc Güell
- Church
- museum
The main tourist attraction factor of the Barcelona brand is its tangible heritage. It can
be observed that the Barcelona brand identity and image are mainly associated with
Gaudí and architecture. Gaudí, his masterpieces and the related subject of architecture
account for more than one half of the tangible heritage mentioned about Barcelona.
8. Urban
environment
20.28%
- ramblas
- metro
- rambla
- market
Within the “urban environment” category the most common element mentioned, as
could be expected, is 8.2 “Barcelona attractions”.
1. Food and Wine 9.11%
- tapas
- wine
- chocolate
- beer
- paella
Barcelona has a good number of restaurants and places to drink. 1.2 “Wine” only
represents 11.26% and the rest belongs to 1.1. “Food and drinks”.
3. Leisure and
Recreation
8.44%
- bar/s
- club
- recovered
- Tibidabo
These two categories (1. “Food and wine” and 3. “Leisure and recreation”) are
considerably present because Barcelona, as a big city, has a great variety of restaurants
and food offer and also a great leisure offer (concerts, theatre, nightlife, festivals, etc.).
6. Sun, Sea and Sand 6.76%
- beach
- port
- sea
- sun
After that comes the identification of Barcelona with attraction factor 6. “sun, sea and
sand” (6,76%), which is comprehensible as Barcelona is a coastal Mediterranean port
city.
5. Sports 3.88%
- Nou Camp
- stadium
- barca
- Olympic
- game
Then we can see that the category of sports in Barcelona is the highest of all brands
(3.88%)
4. Nature and active
tourism
3.19%
- mountain/s
- tree/s
- nature
This factor is low because of the eminently urban nature of the space of the brand.
2. Intangible
Heritage
1.45%
- flamenco
- parade
- siesta
- La Mercè/
Merce
This last category is surprisingly low as Barcelona holds multiple folkloric, traditional
and popular mass celebrations. However, it seems bloggers do not identify the
intangible heritage with the city and its surroundings very strongly, and the little they
do, they associate it with flamenco, parades or siesta which are not traditions of
Catalan origin. The only genuine celebration of Barcelona mentioned is La Mercè.
23,435
T-B&R
entries
3rd level
Barcelona
Indexed
Card
4. Selected results

22. ENTER 2015 PhD Workshop Slide Number 22
23,387 T-B&R entries
3rd level
TOURISM BRAND (j)
Barna CatCe cBarc cBrav cDaur Pyren
TOURISM ATTRACTION FACTORS (i) Location quotient by brand
Sectorial
Localization
coefficient
1. Food and Wine 1.009 0.602 1.991 0.698 0.905 0.930 0.027
2. Intangible Heritage 0.978 0.505 2.592 0.545 1.674 0.747 0.053
3. Leisure & recreation 0.931 0.536 1.174 0.953 2.964 0.518 0.070
4. Nature & active tourism 0.850 5.406 0.959 1.628 1.379 8.428 0.132
5. Sports 1.088 0.486 0.755 0.283 0.373 0.450 0.076
6. Sun, Sea & Sand 0.871 0.362 3.307 1.913 1.784 0.334 0.123
7. Tangible Heritage 1.017 1.077 0.513 1.083 0.685 0.718 0.021
8. Urban Environment 1.054 0.752 0.618 0.642 0.547 0.879 0.047
Coefficient of Specialization 0.022 0.201 0.308 0.133 0.263 0.279
Coefficient of Diversification 0.559 0.603 0.318 0.586 0.412 0.497
4. Selected results
Spatial indexes

23. ENTER 2015 PhD Workshop Slide Number 23
 Tourists mention very popular prominent elements (must-sees), and concentrate on very
specific territories (the region’s capital) while official tourism websites promote elements
of all types and all brand regions.
 Bloggers and reviewers use more attribute-based words and feelings, while official
tourism websites show a more “holistic” image of the destinations, more centered on
general descriptions.
 Cultural identity images transmitted by tourists are highly based on stereotypes,
fragmented and partial.
 Great geographical imbalance or disproportion and specialization of image transmission
of the different sub-regional brand territories.
 Significant dissonances exist in the destination image (Bandyopahyay & Morais, 2005) of
the region and sub-regions studied at the levels of attribute-based identity, cultural
identity and spatial distribution of image.
 Great dissonance in front-nodes between user and destination generated images at
regional and sub-regional levels.
 Multiple representations of the same destination and struggles exist (Andsager &
Drzewicka, 2002) in the online environment (Choi et al., 2007; Krizman & Belullo, 2007).
The perceived image that tourists hold once they have visited a destination does not
correspond to the one constructed and projected by the destinationH1
5. Conclusions

24. ENTER 2015 PhD Workshop Slide Number 24
With the creation of user-generated content and its transmission through the social
media, image perceived by tourists becomes transmitted image and the image
formation circle is increasingly closed from tourist to tourist due to its great potential
influence. User-generated image online has a greater potential to influence than
official destination image.
H2
 Greater visibility and usage of travel blogs and reviews vs. official tourism websites.
 The image perceived by tourists becomes instantly transmitted to other tourists
online in web 2.0 spaces.
 The potential to influence of user-generated contents and the social media is
growing every day due to the increasing creation of contents, their acceptance,
trustworthiness, the capacity of meeting tourists’ needs and interests, and the
many advantages they present for users (Cox et al., 2008).
 The circle of image formation is increasingly taking place in a solely user milieu and
the importance of the different sources throughout the tourist process changes.
 Local organizations’ loss of control over user-generated images. Now, pre-trip
promotion is no longer dominated by outsiders (tour operators) (Dann, 1996) but
by users.
Need for a new paradigm when perceived image becomes transmitted image
5. Conclusions

25. ENTER 2015 PhD Workshop Slide Number 25
5. Conclusions
 Objective method to select the most relevant data sources for the case study and
establishment of a selection criterion according to research goals.
 It includes the analysis of websites’ image dissemination to assess the capacity the
information sources targeted have to disseminate the information they convey.
 Massive analysis of data:
 All travel blogs and reviews about our case study on the websites fulfilling the
criterion.
 key: Creation of a database  Download web pages and entries to the PC, arrange
them into a structure of folders and files. Data cleaning and debugging, language
detection, data mining.
 Quantitative content analysis performed on online texts, based on word counts or
frequencies and word grouping into categories, proved to be a useful and appropriate
method of analysis to shed light on the projected and perceived images of a destination.
 Computerized content analysis through Site Content Analyzer and other software are
suitable to deal with quantitative data and large sets of analysis.
 It enables to look deeper into certain complex aspects, such as cultural identity and the
spatial distribution of tourist image through the adaptation of spatial indexes.
 Methodological framework could be used for other studies whose target were different
destinations and different types of online media and tourist websites, and periods of time.
Utility and benefits of the methodology

26. ENTER 2015 PhD Workshop Slide Number 26
Thanks for your attention!
Estela Mariné-Roig
University Rovira i Virgili, Catalonia, Spain
estela.marine@urv.cat
http://www.urv.cat