系統識別號 | U0002-2606201711130000 |
---|---|
DOI | 10.6846/TKU.2017.00924 |
論文名稱(中文) | 建構以評論中情感為基礎之網路影片熱門度模式 |
論文名稱(英文) | A Sentiment-Based Model for Online Video Popularity |
第三語言論文名稱 | |
校院名稱 | 淡江大學 |
系所名稱(中文) | 企業管理學系碩士班 |
系所名稱(英文) | Department of Business Administration |
外國學位學校名稱 | |
外國學位學院名稱 | |
外國學位研究所名稱 | |
學年度 | 105 |
學期 | 2 |
出版年 | 106 |
研究生(中文) | 傅鴻澤 |
研究生(英文) | Verkholantsev Alexey |
學號 | 604615020 |
學位類別 | 碩士 |
語言別 | 繁體中文 |
第二語言別 | |
口試日期 | 2016-06-01 |
論文頁數 | 155頁 |
口試委員 |
指導教授
-
張瑋倫
委員 - 解燕豪 委員 - 陳立民 |
關鍵字(中) |
線上影片 熱門度 評論 情感分析 |
關鍵字(英) |
Online Video Popularity Comment Sentiment Analysis |
第三語言關鍵字 | |
學科別分類 | |
中文摘要 |
網際網路的普及使不同網路服務自由發展,很多人趁著此機會創立每天用得到的網站或網路平台,而近來像YouTube影片分享網站也愈來愈受歡迎,雖然其提供留言與評估(點選喜歡或不喜歡)影片的功能,但大多數使用者選擇觀看影片或判斷其熱門度時,常將忽略此功能,而只重視影片觀看次數,故本研究期望透過情感分析,探討線上影片中回覆內容情感之影響、瞭解其他可影響到影片熱門度因素之重要性、建構影片能見度以及以情感指標為基礎之影片熱門度模式,並透過問卷發放驗證其對於使用者影片選擇之影響。 本研究共選擇YouTube中八個不同影片類型頻道、306部影片與59,103則回覆,研究共收集200份問卷,而從研究結果可知,觀看次數較高的影片或頻道不見得具有較多正面回覆。此外,納入情感因素後,使用者的影片選擇將有所差異,並聚焦於正負詞比率較高的影片。第三,影片本身因素(如影片標題、縮圖與內容)之影響程度比其他客觀的因素(如觀看次數、喜歡次數與評論中正負詞比率)高。最後,雖然所有因素中情感因素對於影片選擇的影響較低,但其本身影響程度被36.8%填答者選為三分(中度),由此可知,情感因素能影響到對於影片的意見或改變觀看之決策。 此外,由於現今許多商品廣告或行銷公司針對線上影片經營其效益,透過本研究建構的影片熱門度模式進行情感因素有效管理(如得知影片正負面回覆或喜歡次數),以聚焦於情感因素提高影片熱門度及吸引更多新觀看者,最後,以分析與將情感方面的資訊提供予使用者參考提高網路行銷平台之銷效率。 |
英文摘要 |
The spread of Internet provides different new services for development. Today, video-sharing website such as YouTube has become more and more popular. Although it has functions like comment as well as like or dislike most people still neglect them and pay attention only to the number of views. Therefore, this study investigates the influence of online video by focusing on sentiment analysis, understands the importance of other factors that may impact on online video’s popularity, and build a model of online video popularity. This study selected eight different types of channels from YouTube, including 306 videos and 59103 comments. We also collected 200 questionnaires. The result showed that videos with certain views are not always prone to have more positive comments. In addition, the use of sentiment indeed impacted on users’ selection of videos in terms of higher sentimental ratio. Moreover, the influence of factors of video itself (e.g. title, thumbnail or content) is higher than the influence of other factors (e.g. views, likes or sentimental ratio). Although, the influence of sentimental ratio relatively low, the impact was rated as five scale of three by 36.8% respondents. That is, sentiment factor may impact on opinion about the video or even change the selection of videos. Moreover, many product advertisement or marketing companies focus on benefits of online videos. This study can also provide three implications; for instance, by using the proposed video popularity model to help conduct effective sentimental factors management (e.g. to know number of views or likes), increasing video popularity and attracting more viewers, and enhancing marketing efficiency of online video platforms. |
第三語言摘要 | |
論文目次 |
目錄 I 表目錄 II 圖目錄 V 第一章 緒論 1 第一節 研究背景 1 第二節 研究動機 4 第三節 研究問題 7 第四節 研究目的 9 第二章 文獻探討 11 第一節 線上影片(Online Video) 11 第二節 情感分析(Sentiment Analysis) 15 第三章 研究方法 19 第一節 影片熱門度模式(Video Popularity Model) 19 第二節 影片能見度因子(Video Visibility Factor) 22 第三節 情感因子(Sentiment Factor) 24 第四章 資料分析 27 第一節 資料收集 27 第二節 問卷設計與分析 29 第三節 影片留言之情感分析 34 第四節 資料分析 36 一、娛樂類型頻道 36 二、運動類型頻道 54 三、部落格類型頻道 69 四、How to/時髦類型頻道 88 第五章 結論 108 第一節 綜合討論 108 第二節 結論 118 第三節 管理意涵 134 第四節 研究限制 135 參考文獻 137 英文部分 137 網路部分 143 附錄 145 表目錄 表2-1 線上影片研究彙整 14 表2-2 情感研究彙整 18 表3-1影片熱門度模式符號對照表 22 表4-1研究頻道內容彙整 29 表4-2問卷內容與說明 31 表4-3研究樣本之基本資料 32 表4-4看電視、使用網路與YouTube之行為 33 表4-5其他使用YouTube之行為 34 表4-6研究樣本情感分析數據彙整 36 表4-7 Studio C頻道使用者選擇之原始與修正後排行榜 37 表4-8 Studio C頻道原始排行榜所有想觀看中之前三名影片 40 表4-9 Studio C頻道原始排行榜影片因素之影響程度 41 表4-10 Studio C頻道修正後排行榜所有想觀看中之前三名影片 42 表4-11 Studio C頻道修正後排行榜影片因素之影響程度 43 表4-12 Studio C頻道原始與修正後排行榜對照表 44 表4-13 Studio C頻道原始與修正後排行榜所有想觀看中之前三名影片 45 表4-14 NatesLife頻道使用者選擇之原始與修正後排行榜 46 表4-15 NatesLife頻道原始排行榜所有想觀看中之前三名影片 48 表4-16 NatesLife頻道原始排行榜影片因素之影響程度 49 表4-17 NatesLife頻道修正後排行榜所有想觀看中之前三名影片 50 表4-18 NatesLife頻道修正後排行榜影片因素之影響程度 51 表4-19 NatesLife頻道原始與修正後排行榜對照表 52 表4-20 NatesLife頻道原始與修正後排行榜所有想觀看中之前三名影片 53 表4-21 Studio C與NatesLife頻道對照表 53 表4-22 Wrzzer頻道使用者選擇之原始與修正後排行榜 55 表4-23 Wrzzer頻道原始排行榜所有想觀看中之前三名影片 56 表4-24 Wrzzer頻道原始排行榜影片因素之影響程度 57 表4-25 Wrzzer頻道修正後排行榜所有想觀看中之前三名影片 58 表4-26 Wrzzer頻道修正後排行榜影片因素之影響程度 60 表4-27 Wrzzer頻道原始與修正後排行榜對照表 60 表4-28 Wrzzer頻道原始與修正後排行榜所有想觀看中之前三名影片 61 表4-29 Copa90頻道使用者選擇之原始與修正後排行榜 61 表4-30 Copa90頻道原始排行榜所有想觀看中之前三名影片 63 表4-31 Copa90頻道原始排行榜影片因素之影響程度 64 表4-32 Copa90頻道修正後排行榜所有想觀看中之前三名影片 66 表4-33 Copa90頻道修正後排行榜影片因素之影響程度 67 表4-34 Copa90頻道原始與修正後排行榜對照表 67 表4-35 Copa90頻道原始與修正後排行榜所有想觀看中之前三名影片 68 表4-36 Wrzzer與Copa90頻道對照表 69 表4-37 AlishaMarieVlogs頻道使用者選擇之原始與修正後排行榜 70 表4-38 AlishaMarieVlogs頻道原始排行榜所有想觀看中之前三名影片 73 表4-39 AlishaMarieVlogs頻道原始排行榜影片因素之影響程度 74 表4-40 AlishaMarieVlogs頻道修正後排行榜所有想觀看中之前三名影片 76 表4-41 AlishaMarieVlogs頻道修正後排行榜影片因素之影響程度 77 表4-42 AlishaMarieVlogs頻道原始與修正後排行榜對照表 78 表4-43 AlishaMarieVlogs頻道原始與修正後排行榜所有想觀看中之前三名影片 78 表4-44 The Gabbie Vlogs頻道使用者選擇之原始與修正後排行榜 79 表4-45 The Gabbie Vlogs頻道原始排行榜所有想觀看中之前三名影片 82 表4-46 The Gabbie Vlogs頻道原始排行榜影片因素之影響程度 83 表4-47 The Gabbie Vlogs頻道修正後排行榜所有想觀看中之前三名影片 84 表4-48 The Gabbie Vlogs頻道修正後排行榜影片因素之影響程度 86 表4-49 The Gabbie Vlogs頻道原始與修正後排行榜對照表 86 表4-50 The Gabbie Vlogs頻道原始與修正後排行榜所有想觀看中之前三名影片 87 表4-51 AlishaMarieVlogs與The Gabbie Vlogs頻道對照表 88 表4-52 alpha m.頻道使用者選擇之原始與修正後排行榜 89 表4-53 alpha m.頻道原始排行榜所有想觀看中之前三名影片 92 表4-54 alpha m.頻道原始排行榜影片因素之影響程度 93 表4-55 alpha m.頻道修正後排行榜所有想觀看中之前三名影片 94 表4-56 alpha m.頻道修正後排行榜影片因素之影響程度 96 表4-57 alpha m.頻道原始與修正後排行榜對照表 96 表4-58 alpha m.頻道原始與修正後排行榜所有想觀看中之前三名影片 97 表4-59 teachingmensfashion頻道使用者選擇之原始與修正後排行榜 98 表4-60 teachingmensfashion頻道原始排行榜所有想觀看中之前三名影片 100 表4-61 teachingmensfashion頻道原始排行榜影片因素之影響程度 101 表4-62 teachingmensfashion頻道修正後排行榜所有想觀看中之前三名影片 103 表4-63 teachingmensfashion頻道修正後排行榜影片因素之影響程度 104 表4-64 teachingmensfashion頻道原始與修正後排行榜對照表 105 表4-65 teachingmensfashion頻道原始與修正後排行榜所有想觀看中之前三名影片 106 表4-66 alpha m.與teachingmensfashion頻道對照表 106 表5-1 Studio C與NatesLife頻道因素互相影響程度之對照表 109 表5-2 Wrzzer與Copa90頻道因素互相影響程度之對照表 112 表5-3 AlishaMarieVlogs與The Gabbie Vlogs頻道因素互相影響程度之對照表 114 表5-4 alpha m.與teachingmensfashion頻道因素互相影響程度之對照表 117 表5-5基本資料與YouTube互動體驗和影響到影片選擇因素之關聯性 121 表5-6 Studio C頻道不同年齡區間填答者原始與修正後排行榜之選擇行為 123 表5-7 NatesLife頻道不同年齡區間填答者原始與修正後排行榜之選擇行為 124 表5-8 Wrzzer頻道不同年齡區間填答者原始與修正後排行榜之選擇行為 125 表5-9 Copa90頻道不同年齡區間填答者原始與修正後排行榜之選擇行為 126 表5-10 AlishaMarieVlogs頻道不同年齡區間填答者原始與修正後排行榜之選擇行為 127 表5-11 The Gabriel Vlogs頻道不同年齡區間填答者原始與修正後排行榜之選擇行為 129 表5-12 alpha m.頻道不同年齡區間填答者原始與修正後排行榜之選擇行為 130 表5-13 teachingmenfashion頻道不同年齡區間填答者原始與修正後排行榜之選擇行為 132 圖目錄 圖1-1 YouTube全球使用者分佈比率前五名國家 2 圖1-2 YouTube全球訂閱者人數最多之頻道 3 圖4-1問卷排行榜分配方法 30 圖4-2 Studio C頻道使用者偏好之原始排行榜 39 圖4-3影響觀看Studio C頻道原始排行榜影片選擇因素 40 圖4-4 Studio C頻道使用者偏好之修正後排行榜 41 圖4-5影響觀看Studio C頻道修正後排行榜影片選擇因素 43 圖4-6 NatesLife頻道使用者偏好之原始排行榜 48 圖4-7影響觀看NatesLife頻道原始排行榜影片選擇因素 49 圖4-8 NatesLife頻道使用者偏好之修正後排行榜 50 圖4-9影響觀看NatesLife頻道修正後排行榜影片選擇因素 51 圖4-10 Wrzzer頻道使用者偏好之原始排行榜 56 圖4-11影響觀看Wrzzer頻道原始排行榜影片選擇因素 57 圖4-12 Wrzzer頻道使用者偏好之修正後排行榜 58 圖4-13影響觀看Wrzzer頻道修正後排行榜影片選擇因素 59 圖4-14 Copa90頻道使用者偏好之原始排行榜 63 圖4-15影響觀看Copa90頻道原始排行榜影片選擇因素 64 圖4-16 Copa90頻道使用者偏好之修正後排行榜 65 圖4-17影響觀看Copa90頻道修正後排行榜影片選擇因素 66 圖4-18 AlishaMarieVlogs頻道使用者偏好之原始排行榜 72 圖4-19影響觀看AlishaMarieVlogs頻道原始排行榜影片選擇因素 74 圖4-20 AlishaMarieVlogs頻道使用者偏好之修正後排行榜 75 圖4-21影響觀看AlishaMarieVlogs頻道修正後排行榜影片選擇因素 76 圖4-22 The Gabbie Vlogs頻道使用者偏好之原始排行榜 81 圖4-23影響觀看The Gabbie Vlogs頻道原始排行榜影片選擇因素 82 圖4-24 The Gabbie Vlogs頻道使用者偏好之修正後排行榜 83 圖4-25影響觀看The Gabbie Vlogs頻道修正後排行榜影片選擇因素 85 圖4-26 alpha m.頻道使用者偏好之原始排行榜 91 圖4-27影響觀看alpha m.頻道原始排行榜影片選擇因素 92 圖4-28 alpha m.頻道使用者偏好之修正後排行榜 94 圖4-29影響觀看alpha m.頻道修正後排行榜影片選擇因素 95 圖4-30 teachingmensfashion頻道使用者偏好之原始排行榜 99 圖4-31影響觀看teachingmensfashion頻道原始排行榜影片選擇因素 101 圖4-32 teachingmensfashion頻道使用者偏好之修正後排行榜 102 圖4-33影響觀看teachingmensfashion頻道修正後排行榜影片選擇因素 103 |
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