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    Please use this identifier to cite or link to this item: http://ir.cnu.edu.tw/handle/310902800/32957

    標題: 以社會網絡分析方法探討臺南景點之網絡關係
    Discussion on the Network Relation of Tainan Attractions for Social Network Analysis Method
    作者: 鄭宇琁
    貢獻者: 休閒保健管理系
    關鍵字: 社會網絡分析
    social network
    sightseeing route
    日期: 2019
    上傳時間: 2020-12-09 14:41:46 (UTC+8)
    摘要: 本研究旨在探討臺南之觀光旅遊發展,研究內容分成兩個部份,第一部份為臺南旅遊人次分析,第二部份為旅遊景點網絡分析。
    This study was aimed to investigate the development of tourism in Tainan. This study comprised two parts, including an analysis of the number of visitors to Tainan and a network analysis of tourist attractions.
    Firstly, based on the statistics released by Tourism Bureau of Tainan City Government, this study explained the changes in the number of visitors to famous tourist attractions in recent years. Results showed that Nankunshen Daitan Temple, Madou Daitan Temple, and Chihkan Tower are the top three tourist attractions in terms of the total number of visitors, suggesting that the religious type of attractions is relatively more popular among tourists. This study further classified tourist attractions into three groups, including religious, artistic, and recreational. Nankunshen Daitan Temple ranked first in the religious group, Chimei Museum was at the top in the artistic group, and Guanziling Hot Spring Area topped the recreational group. In terms of tourism growth, Beimen Visitor Center enjoyed the largest growth in the number of visitors over the past years.
    Secondly, this study applied social network analysis to investigate the sightseeing routes recommended by the government. A total of 23 itineraries recommended Tourism Bureau of Tainan City Government were included in the analysis. Using UCINET as the instrument, this study created the social network diagram of tourist attractions and calculated the closeness centrality and betweenness centrality between tourist attractions to understand the representativeness of each tourist attraction of each sightseeing route. Further, this study compared the analysis results with the actual status obtained in the first stage and then proposed suggestions for improvement.
    This study utilized UCINET, the most widely adopted software for social network analysis, to draw a relationship network of tourist attractions with data arrays. The relations between tourist attractions were determined based on collected sightseeing routes. In the relationship matrix, 1 indicates presence of a link between two tourist attractions, and 0 indicates absence of a link between two tourist attractions. Based on the matrix, this study used the centrality metric to calculate degree centrality, closeness centrality, and betweenness centrality of each tourist attraction for further discussion and analysis.
    The results offered insights into the network connectivity between popular tourist attractions in Tainan City and might be helpful for the public department in allocation of resources and adjustment of suggested itineraries.
    關聯: 電子全文公開日期:2019-07-22
    學年度:107, 52頁
    Appears in Collections:[休閒保健管理系(所)] 博碩士論文

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