Reconsidering Tourism Destination Images by Exploring Similarities between Travelogue Texts and Photographs
Abstract
:1. Introduction
- We use NLP and image caption technology to analyze the destination image perception from texts and photographs as data sources in travelogues, respectively.
- We compare the differences exhibited by the two forms of data, text, and image, in the perception of TDIs.
- We propose a scientific basis for the selection of data sources and measurement methods for future TDI perception.
2. Theoretical Background
2.1. Tourism Destination Image and Marketing Communication
2.2. Conceptualizing Tourism Destination Image Formation
2.3. Travelogues in TDI Research
2.4. Research on Photograph-Based TDIs
3. Materials and Methods
3.1. Destination Choice
3.2. Data Acquisition and Preprocessing
3.3. Methodology
3.3.1. Image Caption Generation
3.3.2. Natural Language Processing (NLP) Technology
3.3.3. LDA Topic Model
3.3.4. Social Networks Analysis
4. Results and Analysis
4.1. Analysis of Overall Perception
4.2. Analysis of Image Formation
5. Discussion
- (1)
- Unlike the TDI research conducted by Cherem et al. [72,73,84], which was based on mere text or photograph data sources, our research focuses on both the textual and visual information of UGC travelogues to present a framework of summarizing TDI, thus enriching the data sources and methods. Similar to the content analysis methods by mining the user-generated textual and visual information of Pang et al. [33,55,99], our research considers two types of data in travelogues, namely texts and photographs, and compares their similarities and differences in TDI research. Somewhat differently, we used a machine learning approach and image caption technology to describe the content of a photograph in natural language, allowing for a more efficient and objective analysis of larger volumes of photographic data. The similarities and differences of these data sources in the content analysis, from the perspective of semiotics, show the effectiveness and science of the proposed TDI summarization framework for tourism destination image mining and marketing.
- (2)
- Meanwhile, as cities imposed COVID-19-related quarantine measures, long-distance travel came to a complete halt. Many scholars examined the tourists’ perception of the destination image while stranded during the COVID-19 pandemic and analyzed the factors influencing the destination image and visit intention in the post-COVID-19 crisis recovery [100,101,102]. However, from the perspective of methods, traditional questionnaire surveys and expert interviews are still the mainstream. To fill this gap, we compared the heterogeneity and substitutability between text-based and photograph-based TDI research through NLP and image caption technologies, taking the niche destination Tiantai as an example. Hence, scholars can examine and construct TDIs during and after the COVID-19 pandemic with more objective and comprehensive methods.
- (1)
- In order to find their own brand image positioning, scenic spot operators and other relevant parties need to make reasonable use of UGC and other data sources through more effective data processing techniques. After summarizing the brand image perception of a location based on the results, especially image formation, it shows that the iconic signs, such as Tiantai’s magnificent scenery and Buddhist culture, leave the deepest impression on tourists. Thus, marketing suggestions can be given to the relevant parties of the tourism location to improve the image of the tourism destination and further improve the willingness to travel: when branding in the local area, according to the current TDI of the public, the consistency and continuity of the brand image of the tourism destination should be kept [103].
- (2)
- On the basis of respecting tradition and inheriting the original brand image, it is more important to create a new destination brand image. That is, developing and discovering potentially popular future brand attributes based on our research findings. The homogenization of the Chinese tourism market is serious, which will make tourist destinations less competitive. The changing times and the changing characteristics of the visitor group will bring new meanings to the destination brand image. It is especially important to learn from the successful experiences of other tourism destinations’ development and find individual competitive advantages.
- (1)
- Government should pay more attention to the “peripheral tourism” market and build the associated infrastructure. In the era of big data, we should not only consider the resources and cultural characteristics of the tourist destination itself but also fully consider the tourists’ perception of the destination [90]. From the results of the study, we fully affirm the importance of tourists’ perceptions of TDIs. However, from an objective point of view, we cannot deny that, in the context of the epidemic, tourists will be more sensitive to the distance of the destination, the choice of transportation, and the decision about the length of stay. Self-driving and public transportation have replaced traditional tourist trunk transportation in the peripheral tour, and the role of tour guides will basically fade out of the peripheral tour market with the change in the high frequency and lifestyle of consumers’ peripheral tours. At the same time, the accommodation factor has become the most important issue for peripheral tourism users. There will be a huge potential for precise guidance on food and beverages, tickets, entertainment, and leisure items based on accommodation. To revitalize the tourism industry, governments and stakeholders should meet the needs of “customers” based on the image of the destination.
- (2)
- It is significant for the government to play a role in precise marketing promotion and, thus, help build TDIs. For the government, tourism activities are mostly planned for specific scenic spots; thus, developing a five-stage location marketing and digital marketing strategy to enhance the overall competitiveness of local tourism will be effective [104,105].
6. Conclusions
7. Limitation and Future Work
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Texts | Images | ||
---|---|---|---|
Adj. | Frequency | Repeated Descriptions | Frequency |
nice | 183 | a waterfall that is in the middle of a river | 254 |
famous | 100 | a vase filled with flowers on top of a tree | 244 |
wonderful | 81 | a car parked on the side of a road | 226 |
huge | 73 | a series of photographs showing different types of shots | 149 |
unique | 70 | a scenic view of a river with mountains | 116 |
spectacular | 65 | a mountain range with a mountain range behind it | 112 |
clean | 60 | a mountain range with trees and mountains | 111 |
comfortable | 55 | a plate of food on a table | 92 |
fresh | 54 | a building with a clock on the front of it | 78 |
limpid | 52 | a large building with a clock on the side of it | 68 |
Topic 1 (51%) | Topic 2 (22.4%) | Topic 3 (18.1%) | Topic 4 (8.5%) |
---|---|---|---|
Tiantai | tickets | waterfall | Lushan |
Kokuseiji Temple | highway | upstream | Serpentine Island savage Cave |
Jigong | hotel | Shuangsi | Serpentine Island pirate Village |
Tiantai Mountain | entrance | pig | Taizhou Fucheng |
scenic | hour | Cloud Tea | Ziyang Street |
sight | driver | tea leaves | Ancient South Yellow Road |
Huading Mountain | spot | gap | Emei Mountain |
Buddhism | night | canyon | far continent |
Shilang Waterfall | morning | tea picking | Luju |
Jigong’s former residence | gate | terracing | Aquilon |
Qiongtai Fairy Valley | 602 | Tongbai Palace | 116 |
---|---|---|---|
Shilang Waterfall | 446 | Shiliang Scenic Spot | 100 |
Chicheng Hill | 302 | Huading National Forest Park | 95 |
Jigong’s former residence | 242 | Houan Village | 95 |
Shenxianju Scenic Spot | 170 | Guoqing Scenic Spot | 90 |
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Zhang, X.; Lu, X.; Zhou, X.; Shen, C. Reconsidering Tourism Destination Images by Exploring Similarities between Travelogue Texts and Photographs. ISPRS Int. J. Geo-Inf. 2022, 11, 553. https://doi.org/10.3390/ijgi11110553
Zhang X, Lu X, Zhou X, Shen C. Reconsidering Tourism Destination Images by Exploring Similarities between Travelogue Texts and Photographs. ISPRS International Journal of Geo-Information. 2022; 11(11):553. https://doi.org/10.3390/ijgi11110553
Chicago/Turabian StyleZhang, Xin, Xiaoqian Lu, Xiaolan Zhou, and Chaohai Shen. 2022. "Reconsidering Tourism Destination Images by Exploring Similarities between Travelogue Texts and Photographs" ISPRS International Journal of Geo-Information 11, no. 11: 553. https://doi.org/10.3390/ijgi11110553