Xi’an tourism destination image analysis via deep learning

Sheng, Fangqing; Zhang, Yang; Shi, Cheng; Qiu, Mengyuan; Yao, Shuaizhen

doi:10.1007/s12652-020-02344-w

Cited by 16 publications

(6 citation statements)

References 38 publications

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“…Two interviewees mentioned TikTok, China’s top short-form video app, enabling users to view and edit videos with music and effects. Processed videos can be enticing, showing unintended marketing made by previous tourists’ video uploads which propel many places to be popular travel destinations (Sheng et al , 2020). One interviewee revealed that she followed several internet celebrities on Weibo and would ask for a place to visit after watching.…”

Section: User Experiencementioning

confidence: 99%

Information search behavior among Chinese self-drive tourists in the smartphone era

Ni¹,

Rhim²,

Chiu³

et al. 2021

IDD

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Purpose The Chinese economy has grown rapidly over the past decade, making self-drive tours more affordable among Chinese tourists. Thus, self-driving tours using online tourism-related information have also been popular. This study aims to investigate information search behaviors among different segments of Chinese self-drive tourists under the influence of contemporary mobile internet technologies and compares the results with prior related studies from a global standpoint. Design/methodology/approach This paper investigates the relationships between tourist demographics and information search behavior in Mainland China based on a quantitative method. This study collected 228 surveys from users with self-drive tour experience. This study also conducted a series of online interviews to explore the potential barriers when self-drive tourists search for information. Findings The results showed variances within pre-decision and post-decision stages between different age groups, social classes and experience levels. Preference for up-to-date information and contemporary platforms were also observed. Originality/value Research paucity exists on self-drive tourists’ information search behavior, using data collected from Mainland Chinese tourists using mobile devices. The findings offer insights to industry practitioners, such as travel agencies and liaison websites, for refining their services to meet the information needs of Chinese self-drive tourists through more comprehensive marketing strategies.

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Section: User Experiencementioning

confidence: 99%

Information search behavior among Chinese self-drive tourists in the smartphone era

Ni¹,

Rhim²,

Chiu³

et al. 2021

IDD

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“…Generally, the function of hashtags on social media platforms like TikTok, Instagram, and Twitter serves to (1) assist users in finding and interacting with content that is relevant and appealing to them; (2) Enable users to participate in global challenges and trends, creating unity and cohesion in shared content; (3) Connect users with similar interests and preferences, facilitating the formation of virtual communities and discussions (Nautiyal et al, 2022;Zhang, 2021). Based on these functions, hashtags can assist tourist destinations in promoting positive attributes and unique experiences offered by the destination (Chenchen, Yurong, Die, & Zhenqiang, 2020;Sheng, Zhang, Shi, Qiu, & Yao, 2020). Considering the vital role of hashtags in forming and managing destination images by connecting tourist experiences and perceptions with marketing communication strategies, in-depth research is needed to understand how tourists and marketers interact through the use of hashtags and how the role of hashtags can be optimized (Nautiyal et al, 2022;Wengel et al, 2022).…”

Section: Tiktok and Hashtagmentioning

confidence: 99%

Empirical Analysis of Destination Image Through Tiktok Video Comments

Sobarna

2023

JTOSPOLBAN

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This study examines the role of comments on the TikTok social media platform in shaping the image of tourist destinations, focusing on Borobudur Temple, a world heritage site in Indonesia. A thematic analysis of comments on TikTok reveals the public's perception of Borobudur Temple as a historical destination enriched with spiritual values and myths. Terms such as "myth" and "belief" predominate, highlighting the temple's uniqueness and religious backdrop. Social media, particularly TikTok, plays a crucial role in shaping these perceptions. By understanding and addressing these perceptions, marketing strategies on digital platforms can be more effective, enhancing the global appeal of Borobudur Temple. The overall findings underscore the power of social media in shaping the image of tourist destinations and provide recommendations for stakeholders in the tourism industry.

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“…S.giglio also uses geo-located images provided by Flickr to understanding relationship between human mobility and touristic attractions through ML clustering algorithm. AI based image building developed by [12]played a game-changing role in Xian city tourism marketing. information provided in the users profiles this affect the performance of model [14].…”

Section: Ai Based Destination Studymentioning

confidence: 99%

ATiTHi: A Deep Learning Approach for Tourist Destination Classification using Hybrid Parametric Optimization

Tejaswini Bhosale

2023

IJRITCC

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A picture is best way to explore the tourist destination by visual content. The content-based image classification of tourist destinations makes it possible to understand the tourism liking by providing a more satisfactory tour. It also provides an important reference for tourist destination marketing. To enhance the competitiveness of the tourism market in India, this research proposes an innovative tourist spot identification mechanism by identifying the content of significant numbers of tourist photos using convolutional neural network (CNN) approach. It overcomes the limitations of manual approaches by recognizing visual information in photos. In this study, six thousand photos from different tourist destinations of India were identified and categorized into six major categories to form a new dataset of Indian Trajectory. This research employed Transfer learning (TF) strategies which help to obtain a good performance measure with very small dataset for image classification.VGG-16, VGG-19, MobileNetV2, InceptionV3, ResNet-50 and AlexNet CNN model with pretrained weight from ImageNet dataset was used for initialization and then an adapted classifier was used to classify tourist destination images from the newly prepared dataset. Hybrid hyperparameter optimization employ to find out hyperparameter for proposed Atithi model which lead to more efficient model in classification. To analyse and compare the performance of the models, known performance indicators were selected. As compared to the AlexNet model (0.83), MobileNetV2(0.93), VGG-19(0.918), InceptionV3(0.89), ResNet-50(0.852) the VGG16 model has performed the best in terms of accuracy (0.95). These results show the effectiveness of the current model in tourist destination image classification.

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Xi’an tourism destination image analysis via deep learning

Cited by 16 publications

References 38 publications

Information search behavior among Chinese self-drive tourists in the smartphone era

Information search behavior among Chinese self-drive tourists in the smartphone era

Empirical Analysis of Destination Image Through Tiktok Video Comments

ATiTHi: A Deep Learning Approach for Tourist Destination Classification using Hybrid Parametric Optimization

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