• Journal of the Korean Institute of Landscape Architecture
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• v.41 no.4
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• pp.42-55
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• 2013

The purpose of this study is to figure out the place characteristics of preferable city tourist attractions through the contents analysis of non-academic literatures such as tourist guidebooks and web materials. The most preferable Seoul tourist attractions were selected by their frequency in literatures including Namsan and Hangang as 'natural' places, Dugsu Palace and Gyungbok Palace as 'historical' places, Itaewon and Daehak-ro as 'lively-cultural' places that were classified by their relativistic character. The main findings of the research are as follows. The essential place characteristics of tourist attractions were synthesized in urban, regional and place scale respectively. While 'contrast' was found to be the most distinguished character of the tourist attractions in the urban context, 'connectivity' was found to be the most distinguished character of the tourist attractions in the regional context. In addition, both 'visibility' and 'experience' were found to be the most distinguished characters of the tourist attractions in the place context. The characteristics of these places seem to be the universal fascination factors of city tourist attractions currently recognized by ordinary citizens. We expect to further strengthen the city identity and the city tourism effect by adopting those research results systematically to the urban environment. Therefore, it is needed to vitalize the urban tourist attractions that we make them to be more 'contrasting' with urban areas surrounding them, more 'connective' with vicinity areas and more 'visibly fascinating' and 'experienced actively and meaningfully' in each place of tourist attractions.

• Journal of Smart Tourism
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• v.1 no.2
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• pp.19-25
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• 2021

Before COVID-19, tourist destinations have experienced problems with congestion of both famous tourist attractions and public transportation. Over-tourism is not an issue at this time, but it is likely to rekindle after the COVID-19 pandemic ends. One method of mitigating over-tourism is to estimate tourist behavior using a tourist transition model and consequently adjust public transportation operations. In this study, we propose a construction method for a model of tourist transitions among tourist attractions based on tourist GPS trajectory data. We construct tourist transition models using actual trajectory data for tourists staying in the vicinity of Kyoto City. The results verify the model performance.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.113-119
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• 2020

Numerous tourist-related data produced on the Internet contain not only simple tourist information but also diverse ideas and opinions from users. In order to derive meaningful information about tourist sites from such big data, the social network analysis of tourist keywords can identify the frequency of keywords and the relationship between keywords. Thus, it is possible to make recommendations more suitable for users by utilizing the clear recommendation criteria of tourist attractions and the relationship between tourist attractions. In this paper, a recommendation system was designed based on tourist site information through big data social network analysis. Based on user personality information, the types of tourism suitable for users are classified through deep learning and the network analysis among tourist keywords is conducted to identify the relationship between tourist attractions belonging to the type of tourism. Tour information for related tourist attractions shown on SNS and blogs will be recommended through tagging.

• Journal of Distribution Science
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• v.12 no.9
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• pp.53-63
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• 2014

Purpose - The rapid spread of SNS and increase of SNS users have heralded great changes in the tourism industry. Therefore, this study focused on how SNS characteristics- usefulness, convenience, interactivity, and intimacy - influence diffusivity, reliability and, consequently, user's preference for tourist attractions. Research design, data, and methodology - This study is designed not only to collect data with a questionnaire survey but also to test hypotheses with SEM by SPSS 18.0 and AMOS 18.0. Results - Usefulness, interactivity, and intimacy positively affect diffusivity, whereas convenience does not positively affect diffusivity. In addition, intimacy has a negative influence on reliability. However, diffusivity and reliability have positive impacts on the preference for tourist places. Conclusions - Certain characteristics of SNS facilitates the spreading of SNS tourist information. Usability and interactivity have positive impacts on the reliance of tourist information. Better communication can enhance the reliance of travel information. The influence of spreading tourist information has a positive influence on its reliance. Extension and reliance can have positive effects on the preference for tourist attractions.

• The Journal of the Korea Contents Association
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• v.16 no.11
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• pp.477-487
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• 2016

In 1995, the filming location of the drama had been famous, and as a result it brings the effect of increasing tourists of that areas. After that, many local governments try to host the filming on their regions to be potential tourist attractions. With the same stream, Jeonju also has attempted to host International Film Festival and to set up Jeonju Film Commission and Jeonju Cinema Complex. However, although the city already has rich infrastructure facilities to make films, the city hardly tries to use the filming locations as tourist attractions. This study suggests four ways of using filming locations as tourist attractions to activate Jeonju economy and improve Jeonju's cultural image. We firstly collect social bigdata related with tourists of filming locations and tourist attractions in Jeonju from Twitter, which is the most representative SNS, and then perform frequency and trend analysis. We also investigate major factors of visits to tourist's attractions based on content analysis of tweet mentions.

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.494-506
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• 2013

Media like TV programs and movies has deeply rooted in the public and it can supply affluent informations on special tourist attractions during short time relatively. Media can make the image of special objects and destinations recreated and viewers induced to the special places. Because of these positive effects, many countries and self governing bodies having tried place marketing through media have done their best to raise the image of their tourist attractions and induce a visit. So, most of studies about the effect relations between media and tourist attractions have been done about the confirmation of the impact relation between media and the image raising of tourist attractions and between media and the tourists's visit inducement. This study reconfirms the results of the existing studies and confirms whether the difference of media program genre causes that of the impact relation between media and the image raising of tourist attractions and between media and the tourists's visit inducement. In order to confirm these purposes, 3 assumptions are established and are proved through statistical analyses based on a questionnaire. According to the results of these analyses, all of 3 established assumptions : assumption 1, the impact relation between media program genres and the image of tourist attraction, assumption 2, the impact relation between the image of tourist attractions and behavior intention, and assumption 3, the impact relation between media program genres and behavior intention, are partly accepted.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.61-68
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• 2021

The development of the fourth industry has enabled users to quickly share a lot of data online. We can analyze big data on information about tourist attractions and users' experiences and opinions using artificial intelligence. It can also analyze the association between characteristics of users and types of tourism. This paper analyzes individual characteristics, recommends customized tourist sites and proposes a system to provide the sacred texts of recommended tourist sites as AR services. The system uses machine learning to analyze the relationship between personality type and tourism type preference. Based on this, it recommends tourist attractions according to the gender and personality types of users. When the user finishes selecting a tourist destination from the recommendation list, it visualizes the information of the selected tourist destination with AR.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.3
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• pp.407-413
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• 2020

Participating in exhibitions is one of the major activities for tourists. When selecting their next travel destination after participating in an event, they use map services and social network services, such as blogs, to obtain information about tourist attractions. The map services are location-based recommendations, because they can easily retrieve information regarding nearby places. Blogs contain informative content about tourist attractions, thereby providing content-based recommendations. However, few services consider both location and content. In location-based recommendations, tourist attractions that are not related to the content of the event attended might be recommended. Content-based recommendation has a disadvantage in that events located at a distance might get recommended. We propose an algorithm that considers both location and content, based on information from the Korea Tourism Organization's Linked Open Data (LOD), Wikipedia, and a Korean dictionary. By extracting nouns from the description of a tourist attraction and then comparing them with nouns about other attractions, a content-based relationship is determined. The distance to the event is calculated based on the latitude and longitude of each tourist attraction. A weight selected by the user is used for linear combination with the content-based relationship to determine the preference order of the recommendations.

• The Journal of Information Systems
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• v.31 no.2
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• pp.239-261
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• 2022

Purpose The purpose of this study is to explore and compare changes in tourist opinion during the COVID-19 pandemic. Since the COVID-19 outbreak has caused changes in all areas of our lives, the conditions related to confinement during a lockdown have led to changes in tourists' habits and behaviors. Design/methodology/approach To analyze opinion changes about tourist attractions, this study performed topic modeling by summarizing topics into five dimensions: management, scenery, price, suggestion, and safety; then, based on the topic modeling results, sentiment analysis and emotion analysis were conducted to explore the change of tourists' opinion during the COVID-19 pandemic. Findings According to the results, this study confirmed the pandemic's positive effect on tourists' opinions about attractions after the COVID 19 outbreak. Presumably due to the absence of lines and crowed. Moreover, the dimension 'Safety' started to appear in US tourists' attractions reviews only in the period after the outbreak and during the mass vaccination. These results mean that tourists started to care more about safety due to the impact of the COVID-19 pandemic.

• Journal of the Economic Geographical Society of Korea
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• v.17 no.2
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• pp.366-384
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• 2014

This study aims to investigate the success factors of each market through the case study of Seoul Gwangjang and Jangheung Toyo(saturday) market which have recently developed as tourist attractions among urban and rural traditional markets in Korea. In terms of location, market week, establishment and management of traditional market, Gwangjang is a private and daily market located in the city center of Seoul, and Jangheung Toyo is a public and periodic market located in rural Jeolla Nam-do Province. Nevertheless those differences, two markets have successfully developed as tourist attractions by the complexity of generally common five factors. Those are the factors such as surrounding location of famous tourist attractions, competitive staple goods(items), price competitiveness for goods, roles of local government and(or) public institution, and marketplace promotion through the mass media. These factors will have a significant implication for the development policy from traditional market to tourist market or tourist attraction.