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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 郭年真(Raymond N. Kuo) | |
| dc.contributor.author | Hsiang-Hsuan Chiu | en |
| dc.contributor.author | 邱湘璇 | zh_TW |
| dc.date.accessioned | 2021-06-17T06:03:31Z | - |
| dc.date.available | 2024-03-05 | |
| dc.date.copyright | 2019-03-05 | |
| dc.date.issued | 2019 | |
| dc.date.submitted | 2019-01-28 | |
| dc.identifier.citation | Al-Daihani, S. M., & Abrahams, A. (2018). Analysis of Academic Libraries' Facebook Posts: Text and Data Analytics. Journal of Academic Librarianship, 44(2), 216-225.
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/71569 | - |
| dc.description.abstract | 研究背景:隨著數位網路資訊發達,社會大眾藉由數位網路媒體進行訊息傳播及交換的模式,已融入日常生活。其中的社群媒體網站,除具有記錄發文時間的功能外,也提供社群媒體上使用者相互以按讚、回應或分享方式互動的特性。而不斷尋找更有效政策推廣管道的政府機關,同樣窺見社群媒體使用者眾多、且直接與民眾連結之特性,亦將部分的政策推廣能量,轉往社群媒體,期待能更直接、快速的,將新政策、新措施,以及正確的公共資源利用與觀念等資訊,傳達給社會大眾。目前尚未有研究探討健康相關政策,經政府機關於社群媒體進行推廣後,在社群媒體上議題的資訊發酵方式、民眾參與及意見反應之情形。故本研究希望藉以瞭解健保議題在社群媒體上的傳播與民眾參與情形,並進一步從貼文內容分析社會大眾對特定議題所抱持的情緒與觀感。
研究目的:本研究透過分級醫療議題在社群媒體上訊息發佈與時序性發展,探討社會大眾對於該議題關注的效用;並且將發布貼文的帳號來源歸為五類,進一步研究不同發文來源與其民眾參與或與情感表現的關聯性,從中尋找可供政府機關瞭解民意之管道,最後再對民眾參與特別高的議題進行討論,瞭解其引起社會大眾注意之原因或影響因素。 研究方法:本研究利用Facebook Graph API與人工搜尋方式,擷取2016年9月22日至2018年9月30日間,以內含「分級醫療六大政策」相關關鍵字的Facebook 公開貼文作為研究對象,其關鍵字包含「分級醫療」、「部分負擔」、「雙向轉診」、「電子轉診平台」及「雁行團隊」等。並依照發文帳號其屬性,區分為「政府機關」、「醫療機構」、「新聞媒體」、「其他組織」及「個人帳號」共五類。 觀察各貼文其發布來源,就發文數量與時序間的變化,以及民眾按讚、回應及分享產生之貼文民眾參與情形進行研究。 並利用台大意見詞詞典繁體版(NTUSD-traditional)進行語意傾向之情感分析判斷,判別各篇貼文中,文字表述的情感是正向還是負向的,以觀察不同類別來源所發布之貼文,其內容在情感比重上是否有差異。 研究結果:2016年9月22日至2018年9月30日間,對於分級醫療議題的發文,以個人帳號為最多,接著由高至低為新聞媒體、醫療機構及其他組織,政府機關則是五類別中發文數量最低的。 至於發文民眾參與,則以新聞媒體為最高,接著由高至低為個人帳號、政府機關及其他組織,醫療機構則是五類別中平均民眾參與最低的。 情感分析結果,平均最正向的是政府機關,次之是醫療機構,接著由高至低分別為個人帳號、其他組織及新聞媒體。 結論:社群媒體本身的特性,是提供一個可供任何使用者都能夠自由發表意見與看法的虛擬空間平台,研究結果發現「政府機關」、「醫療機構」及「其他機關」雖持續有發布貼文,但其貼文產生之民眾參與度極低;而「新聞媒體」因其產業特性,雖發文數總數並不是最多,但仍是最具民眾參與的發文來源,因此能產生的民眾參與實不容小覷。 此外,研究結果顯示「個人帳號」為發文數最多之來源,且貼文內容可能出現對於分級醫療議題的極端情感,政府機關可考慮將社群媒體納為多方瞭解民意的管道之一。 | zh_TW |
| dc.description.abstract | Background:With advances in digital, internet, and information technology, information dissemination and exchange via digital online media has become a part of everyday life. Social media websites record the time at which posts are made and also allow users to interact via likes, comments, or sharing. Government agencies that have been searching for more effective ways of promoting their policies have perceived that social media have numerous users and enable direct contact with the public. They have thus diverted some of their energy in policy promotion to social media so as to convey new policies, new measures, and correct public resource usage concepts to the public faster and more directly. So far, no research has been conducted on how information is processed and how the public engagement and react with regard to health insurance-related policy information that government agencies release on social media. This study aimed to address this issue and examined the emotions and perceptions regarding certain issues by analyzing the contents of their posts.
Objectives:This study investigated the amount of attention given by the public to information released via social media regarding h the hierarchy of medical care policy and examined any changes in this attention with time. We divided the source accounts of posts into five categories and further analyzed the connections between different post sources and the participation or emotional displays of the public so as to provide government agencies with a means of understanding public opinion. We then discussed issues that received close attention from the public to understand the reasons or influence factors that attract public attention. Methodology:Facebook Graph API and manual searching were employed to collect public Facebook posts made between September 22, 2016 and September 30, 2018 and containing keywords associated with the hierarchy of medical care policy, such as “hierarchical medical system”, “copayment”, “two-way referral” and “e-referral platform”. Based on their attributes, we divided the source accounts of posts into five categories: government agencies, medical institutes, news media, other organizations, and personal accounts. We observed the number of posts made by the different categories as time went by, and we also observed public engagement, which took the form of likes, comments, and sharing posts. Using the traditional Chinese version of the National Taiwan University Semantic Dictionary (NTUSD-traditional), we analyzed the semantic tendencies of posts to determine whether the emotions that they implied were positive or negative. In this way, we investigated whether the emotions portrayed by post content varied with the type of source account. Results:During the study period from September 22, 2016 to September 30, 2018, personal accounts made the most posts regarding the hierarchy of medical care policy, followed by news media, medical institutes, and other organizations; government agencies made the fewest posts. With regard to public engagement, news media posts received the most public attention, followed by personal accounts, government agencies, and other organizations. Posts from medical institutes received the least public engagement. The sentiment analysis results revealed that government agencies posts were the most positive, followed by those from medical institutes, personal accounts, other organizations, and news media. Conclusion:The nature of social media in itself is to provide a virtual platform where any user can freely express their own views and opinions. The results revealed that although government agencies, medical institutes, and other organizations continued to make posts, they received extremely low public engagement. Due to the characteristics of the new industry, the total number of posts made by news media was not the highest, but they received the most public engagement. Thus, their influence cannot be ignored. Furthermore, the results of this study showed that personal accounts were the largest source of posts, but much of the content contained extremely negative emotions toward the hierarchy of medical care policy. Government agencies should thus consider adding social media as one of their means of understanding public opinion. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T06:03:31Z (GMT). No. of bitstreams: 1 ntu-108-R05848013-1.pdf: 3829383 bytes, checksum: 9ee3b87c7d5bc525c517034dba29a514 (MD5) Previous issue date: 2019 | en |
| dc.description.tableofcontents | 口試委員會審定書 #
誌 謝 I 摘 要 II ABSTRACT V 目 錄 VIII 圖目錄 X 表目錄 XI 第壹章 緒論 1 第一節 研究背景與動機 1 第二節 研究目的 2 第貳章 文獻回顧 4 第一節 社群媒體之發展與特性 4 第二節 分級醫療 7 第三節 FACEBOOK 9 第四節 政策推廣管道 11 第五節 民意蒐集管道 13 第六節 社群媒體作為政府機關輿論蒐集之管道 17 第七節 社群媒體在公共議題、健康政策及分級醫療之利用 20 第八節 社群媒體研究方法學 24 第參章 研究設計與方法 31 第一節 研究設計與架構 31 第二節 研究假說 33 第三節 研究對象 34 第四節 資料來源與處理流程 35 第五節 研究變項與操作型定義 37 第六節 統計分析方法 41 第肆章 研究結果 42 第一節 基本分析 42 第二節 時序性分析 44 第三節 情感分析 60 第四節 一方變異數分析(ONE-WAY ANOVA) 69 第五節 內容分析 71 第六節 研究結果小節 79 第伍章 討論 83 第一節 研究方法的討論 83 第二節 社群媒體作為民意蒐集管道之重要性 85 第三節 社群媒體上輿論強度之探討 87 第四節 社群媒體上輿論偏好之探討 90 第五節 公共政策議題與民意分布情形之觀察 92 第六節 研究限制 94 第陸章 結論與建議 95 第一節 結論 95 第二節 建議 97 參考文獻 100 附 錄 107 附錄一、健保署官網之新聞發布清單 107 附錄二、新聞稿詞彙使用次數統計表 112 附錄三、本研究之帳號清單 113 | |
| dc.language.iso | zh-TW | |
| dc.subject | 社群媒體 | zh_TW |
| dc.subject | 政府機關 | zh_TW |
| dc.subject | 健康政策 | zh_TW |
| dc.subject | 分級醫療 | zh_TW |
| dc.subject | 民眾參與度 | zh_TW |
| dc.subject | 情感分析 | zh_TW |
| dc.subject | Public engagement | en |
| dc.subject | Social media | en |
| dc.subject | the hierarchy of medical care | en |
| dc.subject | sentiment analysis | en |
| dc.subject | Government | en |
| dc.subject | Health policy | en |
| dc.title | 健康政策於社群媒體傳播與民眾參與分析-以分級醫療為例 | zh_TW |
| dc.title | The Use and Public Engagement of Social Media in Health Policy:The Case of Hierarchy of Medical Care | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 107-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 陳端容,張鈺旋 | |
| dc.subject.keyword | 社群媒體,政府機關,健康政策,分級醫療,民眾參與度,情感分析, | zh_TW |
| dc.subject.keyword | Social media,Government,Health policy,the hierarchy of medical care,Public engagement,sentiment analysis, | en |
| dc.relation.page | 135 | |
| dc.identifier.doi | 10.6342/NTU201900231 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2019-01-28 | |
| dc.contributor.author-college | 公共衛生學院 | zh_TW |
| dc.contributor.author-dept | 健康政策與管理研究所 | zh_TW |
| 顯示於系所單位: | 健康政策與管理研究所 | |
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|---|---|---|---|
| ntu-108-1.pdf 未授權公開取用 | 3.74 MB | Adobe PDF |
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