| DC 欄位 |
值 |
語言 |
| DC.contributor | 企業管理學系 | zh_TW |
| DC.creator | 馬勝騰 | zh_TW |
| DC.creator | Tomas Setya Wahyu Budi | en_US |
| dc.date.accessioned | 2016-7-14T07:39:07Z | |
| dc.date.available | 2016-7-14T07:39:07Z | |
| dc.date.issued | 2016 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=103421607 | |
| dc.contributor.department | 企業管理學系 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 在競爭激烈的觀光產業中，良好的目的地形象攸關遊客的旅遊選擇與經驗。本研究旨在分析社群網站如推特上的目的地形象資訊，以幫助觀光服務提供者、國家旅遊局能掌握遊客對景點形象的期待及印象。社群網站所提供的公眾意見（如推特資料等），往往能為觀光業者提供大量資訊以利建立與掌握目的地形象。針對倫敦和紐約兩個都市利用文字採礦進行觀念連結的研究分析。本研究進行五個目的地形象特性關鍵字的分析，而這些特性關鍵字可反映推特上公眾意見對這些城市目的地形象的縮影。以關鍵字｢文化｣和｢娛樂｣而言，｢英國文化｣和｢詹姆士龐德｣代表倫敦，而｢黑人文化｣和｢百老匯｣則代表紐約；另一方面，在關鍵字｢節慶｣和｢食物｣中，｢燈光節｣和｢傳統英國菜｣代表倫敦，而｢世界公民節｣和｢食物卡車｣代表紐約。最後，從關鍵字｢購物｣來看， “Etsy”代表倫敦，而“Kate Spade”代表紐約。本研究旨在揭露社群網站分析的重要性和其價值，而文字採礦的方法則是從大量資料中提取公眾意見精華的有效手段。綜上所述，社群網站所提供的資訊可有利觀光業者更有效地建立目的地形象。 | zh_TW |
| dc.description.abstract | In the middle of highly competitive tourism market, development of successful destination image is paramount towards memorable experience for visitors. This study aims to support tourism stakeholders from the service providers and national tourism by analyzing, and extracting meaningful patterns from social media, e.g. Twitter, based on destination image information. This data plays an important role for destination marketers to distinguish their destination among others based on Twitter Statistics and key public opinion towards destination image attributes. London and New York were used as destination cities under the analysis of text mining with the concept linkage approach. Results shows five distinct keywords attributed to each city. Each keyword found to be relevant in representing the image of destination cities based on the public opinion on Twitter. For keyword “Culture and Cultural”, term ＂British” and ＂Black＂ represent London and New York the best, respectively. In keyword “Entertainment”, term ＂James Bond＂ and ＂Broadway＂ represent London and New York, respectively. In keyword “Festival”, term ＂Lumiere＂ and “Global Citizen Festival” are best in describing city of London and New York, respectively. In keyword “Food”, term ＂traditional British food＂ best describes London and ＂Food truck＂ best describes New York. The keyword “Shopping” exhibits term ＂Etsy＂ as the image of London and “Kate Spade＂ as the image for New York. This research reveals the value of social media analysis and the ability of text mining as an effective technique to extract opinions from vast amount of available social media data. Recommendations related to tourism strategic plan are made to facilitate possible future destination image studies. | en_US |
| DC.subject | 目的地形象 | zh_TW |
| DC.subject | 社群網站 | zh_TW |
| DC.subject | 文字採礦 | zh_TW |
| DC.subject | 觀念連結 | zh_TW |
| DC.subject | Destination Image | en_US |
| DC.subject | Social Media | en_US |
| DC.subject | Text Mining | en_US |
| DC.subject | Concept Links | en_US |
| DC.title | 應用社群媒體探勘分析目的地形象的輿論意見 | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.title | Using Social Media Mining to Understand Public Opinion towards Destination Image | en_US |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |