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    請使用永久網址來引用或連結此文件: https://irlib.pccu.edu.tw/handle/987654321/35699


    題名: 陽明山國家公園社群臉書打卡資料分析與應用
    Application and analysis of Facebook check-in big data in Yangmingshan National Park
    作者: 莊哲瑋
    貢獻者: 地學研究所地理組
    關鍵詞: 自願性地理資訊
    社群媒體
    打卡熱門程度
    遊憩區
    時空變化
    日期: 2016
    上傳時間: 2017-03-29 13:05:44 (UTC+8)
    摘要: 陽明山國家公園為北台灣熱門旅遊景點之一,擁有豐富的自然及人文資源,除了提供環境教育外,尚提供多元的遊憩活動,如賞花、健行、泡溫泉及賞夜景等,因此每當假日或特定節日時,便會吸引大量遊客。遊客在旅遊的過程中,經常會利用行動設備來記錄,如拍照及攝影等,甚至透過臉書等相關社群網站的打卡功能來進行個人的生活記錄,因此在社群網站中存在大量個人點位資料,可以用來快速檢視旅遊目的地的熱門程度,只是缺乏系統性檢視大範圍打卡資料的變化情況。本研究將以陽明山國家公園為研究範圍,蒐集並分析 2014年十二月至2016年一月間的打卡資料,討論園內打卡地標的類型及分布,且分析不同時間尺度中打卡數量變化,藉以了解臉書打卡族群在陽明山國家公園的分布與流動。結果發現園內打卡地標多集中道路沿線分布,並以竹子湖及陽明山公車總站周圍最為密集。打卡量易受到活動及季節而有劇烈的變化,如2015年上半年打卡量大部分集中在海拔較低的湖山、陽明公園及竹子湖等地區;下半年的打卡量則集中在七星山、擎天崗及馬槽等地區。在每小時平均打卡變化中,本研究發現園內整體打卡量集中在9至16時之間,並且研究各區打卡量變化後,發現陽明公園與大屯山熔岩台地及馬槽與泉源雖然地理空間不同,卻有相似的打卡量變化,可能與其有相似的遊憩資源有關,如前者為花季,後者為溫泉。最後將打卡量的變化資料與陽管處的遊客統計量比較,發現僅有陽明公園與大屯的打卡變化對遊客統計量具有解釋能力,雖然其他遊憩據點迴歸模型未達顯著,但打卡數據能更細緻的展現園內不同時間尺度之打卡熱門程度的變化,加上近年社群網站的蓬勃發展,故打卡資料用於輔助傳統遊客數量之統計,仍有其重要的功用。
    Yangmingshan National Park is one of Taipei’s most popular tourist attractions, with an abundance of natural and cultural resources. Apart from providing environmental education, it offers diverse recreational activities such as flower appreciation, hiking, hot springs, and night view appreciation among others. Thus, during vacation season or on special holidays, the park attracts many tourists. During their vacation, tourists often use mobile devices to record their activities by taking pictures and videos and often upload their pictures and videos to Facebook and other social media sites, recording their daily activities using check-in. As a result, there is much location-specific information in these social media sites which can be used to quickly gauge the popularity of tourist attractions; the only element missing is a system in place to monitor massive changes in the check-in data. This article uses Yangmingshan National Park as a scope for research, gathers and analyzes check-in data from December 2014 to January 2016, discusses the type and distribution of check-in place, and analyzes the changes in check-in volume using different time scales in order to understand the distribution and movement of Facebook check-in groups in Yangmingshan National Park. As a result of this research, it was discovered that the park’s check-in are mostly distributed along its roads, and many of these are found in the Jhuzihu and Yangmingshan bus terminal areas. The changes in check-in volume are easily influenced by activities and seasons; for example, most of the check-in from the first half of 2015 are concentrated in areas with lower altitudes such as Hushan, Yangming Park, and Jhuzihu, while most of the check-in from the second half of the year are concentrated in the Cising Mountain, Cingtiangang, and Macao recreation areas. Regarding the hourly average changes in check-in this study found that check-in primarily occurs between 9:00 to 16:00, and after analyzing the changes in check-in in different locations, it was discovered that although Yangming Park and the lava structures of Datun Mountain, Macao recreation area, and Quanyuan are geographically dispersed, they have the same volume of check-in changes. This could be due to similarities in their recreational activities (the former has the flower season, and the latter has hot springs). Lastly, the study compares the changes in check-in volume with visitor statistics in Yangming Park, finding that only the check-in changes in Yangming Park and Datun Mountain can explain the visitor statistics data. Although the other recreation-based regression models are not significant, the check-in data can show in detail changes in the park’s level of popularity at different times. In addition, owing to the rapid growth of social media sites in recent years, check-in data are an important supplement to traditional means of calculating visitor volume.
    顯示於類別:[地理學系] 博碩士論文

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