• Title/Summary/Keyword: Tourism Big Data

Search Result 147, Processing Time 0.029 seconds

Subject Association Analysis of Big Data Studies: Using Co-citation Networks (빅데이터 연구 논문의 주제 분야 연관관계 분석: 동시 인용 관계를 적용하여)

  • Kwak, Chul-Wan
    • Journal of the Korean Society for information Management
    • /
    • v.35 no.1
    • /
    • pp.13-32
    • /
    • 2018
  • The purpose of this study is to analyze the association among the subject areas of big data research papers. The subject group of the units of analysis was extracted by applying co-citation networks, and the rules of association were analyzed using Apriori algorithm of R program, and visualized using the arulesViz package of R program. As a result of the study, 22 subject areas were extracted and these subjects were divided into three clusters. As a result of analyzing the association type of the subject, it was classified into 'professional type', 'general type', 'expanded type' depending on the complexity of association. The professional type included library and information science and journalism. The general type included politics & diplomacy, trade, and tourism. The expanded types included other humanities, general social sciences, and general tourism. This association networks show a tendency to cite other subject areas that are relevant when citing a subject field, and the library should consider services that use the association for academic information services.

Framing city image: A content analysis of Chinese city image construction on Korean press

  • YANG Ting;LIU Jing
    • International Journal of Advanced Culture Technology
    • /
    • v.12 no.1
    • /
    • pp.158-168
    • /
    • 2024
  • With Wenhai big data SaaS cloud platform.2.0, this study analyzed data of 135 news reports relating to Chinese city Chongqing from Yonhap News Agency and ten South Korean mainstream newspapers from May 1st, 2018 to September 30th, 2022. Under the framework of Frame Theory, this research conducted data mining and analysis on how Korean mainstream media shaped city image of Chongqing, what kind of city images were shaped from dimensions of politics, economy, society, culture & sports as well as tourism and whether they are consistent with those in Chinese media. At the last part, discussions and suggestions was made.

Analysis of Regional Smart Tourism Status Using Topic Modeling and Network Analysis: Focused on News Articles (토픽 모델링과 네트워크 분석을 활용한 지역별 스마트관광 현황 분석: 뉴스 기사를 중심으로)

  • MuMoungCho Han
    • Smart Media Journal
    • /
    • v.13 no.9
    • /
    • pp.9-17
    • /
    • 2024
  • This study aims to analyze the current status of smart tourism in various regions. To achieve this, 599 news articles containing the keyword 'smart tourism' were collected from national daily newspapers in the BigKinds database, covering the period from January 2014 to June 2024. The collected data was subject to topic modeling based on location, and network analysis was performed using the keyword frequencies in each topic. The topic modeling results identified six major topics: 'Jeju,' 'Incheon,' 'Daegu_Busan_Ulsan,' 'Gyeongju,' 'Suwon,' and 'Yangyang.' It was found that the development of smart tourism in all these regions is centered around tourism projects led by government and local authorities. The network analysis results revealed that 'platform' and 'content' are key keywords related to smart tourism technology across all topics, indicating that these concepts are interconnected to provide services to individual tourists. The findings of this study are expected to provide valuable information for formulating policies and strategies to promote smart tourism in various regions and contribute to the realization of sustainable smart tourism.

Implementation of smart chungbuk tourism based on SNS data analysis (SNS 데이터 분석을 통한 스마트 충북관광 구축)

  • Cho, Wan-Sup;Cho, Ah;Kwon, Kaaen;Yoo, Kwan-Hee
    • Journal of the Korean Data and Information Science Society
    • /
    • v.26 no.2
    • /
    • pp.409-418
    • /
    • 2015
  • With the development of mobile devices and Internet, information exchange has actively been made through SNS and Blogs. Blogs are widely used as a space where people share their experience after their visit to tourist attractions. We propose a method of recommending associated tourist attractions based on tourists' opinions using issue analysis, association analysis, and sentimental analysis for various online reviews including news in order to help to develop tour products and policies. The result shows that north area of Chungbuk province has been selected as issue attractions, and associated attractions/keywards have been identified for given well-known attraction. Positive/negative opinion for review texts has been analyzed and user can grasp the reason for the sentiments. Multidimensional analysis technique has been integrated to derive additional sophisticated insights and various policy proposal for smart tourism.

From Machine Learning Algorithms to Superior Customer Experience: Business Implications of Machine Learning-Driven Data Analytics in the Hospitality Industry

  • Egor Cherenkov;Vlad Benga;Minwoo Lee;Neil Nandwani;Kenan Raguin;Marie Clementine Sueur;Guohao Sun
    • Journal of Smart Tourism
    • /
    • v.4 no.2
    • /
    • pp.5-14
    • /
    • 2024
  • This study explores the transformative potential of machine learning (ML) and ML-driven data analytics in the hospitality industry. It provides a comprehensive overview of this emerging method, from explaining ML's origins to introducing the evolution of ML-driven data analytics in the hospitality industry. The present study emphasizes the shift embodied in ML, moving from explicit programming towards a self-learning, adaptive approach refined over time through big data. Meanwhile, social media analytics has progressed from simplistic metrics deriving nuanced qualitative insights into consumer behavior as an industry-specific example. Additionally, this study explores innovative applications of these innovative technologies in the hospitality sector, whether in demand forecasting, personalized marketing, predictive maintenance, etc. The study also emphasizes the integration of ML and social media analytics, discussing the implications like enhanced customer personalization, real-time decision-making capabilities, optimized marketing campaigns, and improved fraud detection. In conclusion, ML-driven hospitality data analytics have become indispensable in the strategic and operation machinery of contemporary hospitality businesses. It projects these technologies' continued significance in propelling data-centric advancements across the industry.

A Study on the Consumer Perception and Keyword Analysis of Meal-kit Using Big Data

  • Jung, Sunmi;Ryu, Gihwan;Lim, Jeongsook;Kim, Heeyoung
    • International Journal of Internet, Broadcasting and Communication
    • /
    • v.14 no.2
    • /
    • pp.206-211
    • /
    • 2022
  • As the level of consumption is improved and cultural life is pursued, the consumer's consciousness structure is rapidly changing, and the demand for product selection level, variety, and quality is becoming more diverse. The restaurant economy is falling due to the prolonged COVID-19, the economic recession, income decline, and changes in population structure and lifestyle, but the Meal- kit market is growing rapidly. This study aims to identify the consumer perception of Meal-kit, which is rapidly growing as an alternative to existing meals in the fields of dining out, food, and distribution due to the development of technology and social environment using big data. As a result of the analysis, the keywords with the highest frequency of appearance were in the order of Meal-kit, Cooking, Product, Launching, and Market and were divided into 8 groups through the CONCOR analysis. We want to identify consumer trends related to the key keywords of Meal-kit, present effective data related to Meal-kit demand for Meal-kit specialized companies, and provide implications for establishing marketing strategies for differentiated competitive advantage.

Changes in Floating Population Distribution in Jeju Island Tourist Destinations Before and After COVID-19 Using Spatial Big Data Analysis (공간 빅데이터 분석을 활용한 COVID-19 전후 제주도 관광지의 유동인구 분포 변화)

  • Heonkyu Jeong;Yong-Bok Choi
    • Journal of the Korean Association of Geographic Information Studies
    • /
    • v.27 no.1
    • /
    • pp.12-28
    • /
    • 2024
  • This study aims to identify the trend of changes in tourist floating population before and after COVID-19 in major tourist destinations in Jeju Island through spatial analysis. Seongsan-eup and Andeok-myeon in Jeju Island were selected as the research area, and the research period was set at 1 year before and 2 years after the COVID-19 outbreak. For the analysis, mobile floating population data was refined and processed to calculate floating population distribution and floating population increase/decrease data. This was converted into spatial data and an overlay analysis was performed with location data of major tourist attractions. As a result of the analysis, it was confirmed that the floating population of indoor tourist attractions and small facilities decreased immediately after COVID-19, and that in open coastal areas or large facilities, the floating population decreased less or actually increased. In conclusion, in tourism development, it is necessary to identify changes in floating population according to the characteristics of tourist facilities, and it is necessary to develop tourism facilities and strategies that can respond to risk situations such as pandemics when developing tourist destinations.

A Study on the Selection Attributes for Restaurant, Customer Satisfaction, and Recommendation Intention on Traveling Domestic Tourists: Targeting Tourists for Rail-ro Tickets

  • Kim, Ju-Hee;Kang, Kyoung-Ku;Lee, Jong-Ho
    • Culinary science and hospitality research
    • /
    • v.23 no.6
    • /
    • pp.27-35
    • /
    • 2017
  • The purpose of this study was to examine the causal relationship among restaurant selection attributes and customer satisfaction and recommendation tastes for young people in their twenties who use tickets for Rail-ro. Data collection was conducted to utilize questionnaire survey with online and offline distribution. The collected data were analyzed using a statistical program SPSS 21.0 with frequency analysis, reliability analysis, factor analysis, and regression analysis. The results of the study showed that Internet search is the most common source of information about restaurants during the trip, and restaurant choice attributes have an important impact on customer satisfaction, food quality, employee service and reputation, but hygiene did not have a big effect on customer satisfaction. In addition, customer satisfaction has a significant effect on recommendation intention. Concluding the results from this study, it investigated the significant attributes for customers selection of restaurants and provide meaningful advice for market managers to make useful marketing strategies to attract more clients and augment economic benefits.

The study on Analysis of factors of restaurant start-ups using big data

  • JINHO LEE;Sung woo Park;Gi-Hwan Ryu
    • International journal of advanced smart convergence
    • /
    • v.12 no.3
    • /
    • pp.163-167
    • /
    • 2023
  • The restaurant industry is an industry with low entry barriers, and furthermore, it is an indispensable industry in life. However, for the restaurant industry, it is necessary to start a business considering many factors. In particular, the comparative group for each restaurant industry is different, and the commercial area analysis should be analyzed differently. Moreover, counseling for restaurant start-ups is still sticking to how to start a restaurant by meeting with each franchise supervisor or counselor. Therefore, a restaurant start-up chatbot is needed for prospective restaurant founders, and a food tech chatbot is needed to collect basic data. Therefore, in this study, factors for restaurant start-ups were divided into youth, preliminary start-ups, menus, taste, and food. In the case of restaurant start-ups with low entry barriers, it was confirmed as the most preferred start-up by young people. However, indiscriminate restaurant start-ups not only increase the closing rate but also have a significant impact on household debt, so accurate consulting should be used to lower the closing rate and increase the success rate. Furthermore, theories and measures for food technologies such as chatbots should be further developed to obtain accurate information on franchise start-ups.

Identification of Visitation Density and Critical Management Area Regarding Marine Spatial Planning: Applying Social Big Data (해양공간계획 수립을 위한 방문밀집도 및 중점관리지역 규명: 소셜 빅데이터를 활용하여)

  • Kim, Yoonjung;Kim, Choongki;Kim, Gangsun
    • Journal of Environmental Impact Assessment
    • /
    • v.29 no.2
    • /
    • pp.122-131
    • /
    • 2020
  • Marine Spatial Planning is an emerging strategy that promoting sustainable development at coastal and marine areas based on the concept of ecosystem services. Regarding its methodology, usage rate of resources and its impact should be considered in the process of spatial planning. Particularly, considering the rapid increase of coastal tourism, visitation pattern is required to be identified across coastal areas. However, actions to quantify visitation pattern have been limited due to its required high cost and labor for conducting extensive field-study. In this regard, this study aimed to pose the usage of social big data in Marine Spatial Planning to identify spatial visitation density and critical management zone throughout coastal areas. We suggested the usage of GPS information from Flickr and Twitter, and evaluated the critical management zone by applying spatial statistics and density analysis. This study's results clearly showed the coastal areas having relatively high visitors in the southern sea of South Korea. Applied Flickr and Twitter information showed high correlation with field data, when proxy excluding over-estimation was applied and appropriate grid-scale was identified in assessment approach. Overall, this study offers insights to use social big data in Marine Spatial Planning for reflecting size and usage rate of coastal tourism, which can be used to designate conservation area and critical zones forintensive management to promote constant supply of cultural services.