Measuring Destination Image Using AI and Big Data: Kastoria’s Image on TripAdvisor
In recent years, the growing number of Online Travel Review (OTR) platforms and advances in social media and search engine technologies have led to a new way of accessing information for tourists, placing projected Tourist Destination Image (TDI) and electronic Word of Mouth (eWoM) at the heart of t...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
|
| Series: | Societies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-4698/15/1/5 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832587541967011840 |
|---|---|
| author | Anastasia Yannacopoulou Konstantinos Kallinikos |
| author_facet | Anastasia Yannacopoulou Konstantinos Kallinikos |
| author_sort | Anastasia Yannacopoulou |
| collection | DOAJ |
| description | In recent years, the growing number of Online Travel Review (OTR) platforms and advances in social media and search engine technologies have led to a new way of accessing information for tourists, placing projected Tourist Destination Image (TDI) and electronic Word of Mouth (eWoM) at the heart of travel decision-making. This research introduces a big data-driven approach to analyzing and measuring the perceived and conveyed TDI in OTRs concerning the reflected perceptive, spatial, and affective dimensions of search results. To test this approach, a massive metadata analysis of search engine was conducted on approximately 2700 reviews from TripAdvisor users for the category “Attractions” of the city of Kastoria, Greece. Using artificial intelligence, an analysis of the photos accompanying user comments on TripAdvisor was performed. Based on the results, we created five themes for the image narratives, depending on the focus of interest (monument, activity, self, other person, and unknown) in which the content was categorized. The results obtained allow us to extract information that can be used in business intelligence applications. |
| format | Article |
| id | doaj-art-fcd45d0059ca4cf481c440d25f9d7129 |
| institution | Kabale University |
| issn | 2075-4698 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Societies |
| spelling | doaj-art-fcd45d0059ca4cf481c440d25f9d71292025-01-24T13:49:34ZengMDPI AGSocieties2075-46982024-12-01151510.3390/soc15010005Measuring Destination Image Using AI and Big Data: Kastoria’s Image on TripAdvisorAnastasia Yannacopoulou0Konstantinos Kallinikos1Department of Communication and Digital Media, University of Western Macedonia, 52100 Kastoria, GreeceDepartment of Communication and Digital Media, University of Western Macedonia, 52100 Kastoria, GreeceIn recent years, the growing number of Online Travel Review (OTR) platforms and advances in social media and search engine technologies have led to a new way of accessing information for tourists, placing projected Tourist Destination Image (TDI) and electronic Word of Mouth (eWoM) at the heart of travel decision-making. This research introduces a big data-driven approach to analyzing and measuring the perceived and conveyed TDI in OTRs concerning the reflected perceptive, spatial, and affective dimensions of search results. To test this approach, a massive metadata analysis of search engine was conducted on approximately 2700 reviews from TripAdvisor users for the category “Attractions” of the city of Kastoria, Greece. Using artificial intelligence, an analysis of the photos accompanying user comments on TripAdvisor was performed. Based on the results, we created five themes for the image narratives, depending on the focus of interest (monument, activity, self, other person, and unknown) in which the content was categorized. The results obtained allow us to extract information that can be used in business intelligence applications.https://www.mdpi.com/2075-4698/15/1/5destination imagedata miningimage recognitionuser-generated contentprojected imageperceived image |
| spellingShingle | Anastasia Yannacopoulou Konstantinos Kallinikos Measuring Destination Image Using AI and Big Data: Kastoria’s Image on TripAdvisor Societies destination image data mining image recognition user-generated content projected image perceived image |
| title | Measuring Destination Image Using AI and Big Data: Kastoria’s Image on TripAdvisor |
| title_full | Measuring Destination Image Using AI and Big Data: Kastoria’s Image on TripAdvisor |
| title_fullStr | Measuring Destination Image Using AI and Big Data: Kastoria’s Image on TripAdvisor |
| title_full_unstemmed | Measuring Destination Image Using AI and Big Data: Kastoria’s Image on TripAdvisor |
| title_short | Measuring Destination Image Using AI and Big Data: Kastoria’s Image on TripAdvisor |
| title_sort | measuring destination image using ai and big data kastoria s image on tripadvisor |
| topic | destination image data mining image recognition user-generated content projected image perceived image |
| url | https://www.mdpi.com/2075-4698/15/1/5 |
| work_keys_str_mv | AT anastasiayannacopoulou measuringdestinationimageusingaiandbigdatakastoriasimageontripadvisor AT konstantinoskallinikos measuringdestinationimageusingaiandbigdatakastoriasimageontripadvisor |