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系統識別號 U0026-1508201714121300
論文名稱(中文) 運用文字探勘於旅遊部落格意見領袖辨識方法
論文名稱(英文) Identify Opinion Leader in Travel Blogs by Using Text mining.
校院名稱 成功大學
系所名稱(中) 資訊管理研究所
系所名稱(英) Institute of Information Management
學年度 105
學期 2
出版年 106
研究生(中文) 朱峻宏
研究生(英文) Chun-Hung Chu
學號 R76041126
學位類別 碩士
語文別 中文
論文頁數 58頁
口試委員 口試委員-劉任修
口試委員-高宏宇
口試委員-盧文祥
指導教授-王惠嘉
中文關鍵字 文字探勘  意見領袖  情感分析  趨勢分析  大眾分類法 
英文關鍵字 Text Mining  Opinion Leader  Sentiment Analysis  Trend Analysis  Folksonomy 
學科別分類
中文摘要 近年來旅遊已經成為許多人生活中不可或缺的一部分,隨著Web2.0的盛行使用者可以透過部落格發表旅遊相關經驗,然而大量使用者於網上分享內容導致資訊過載的時代來臨,因此讀者傾向於觀看某些自己有興趣的部落客之文章,在特定領域中的熱門部落客即所謂意見領袖,相較於其他評論者通常具有較高的互動性,在社群平台具有不可忽視的影響力。
然而網上的熱門部落客排名往往藉由人氣度來衡量,但部分高人氣部落客是由線上機器人造成,人氣度並非完全可反映其文章的助益性,因缺乏對於部落客文章品質以及社群影響力進行評估,本研究將對於部落客的文章進行情感分析以及趨勢分析,藉由部落客與部落客間的訂閱關係建立社群影響力網路,分析各部落客的重要程度,結合上述因子和人氣度所判定出來的意見領袖將更符合期待,而在旅遊領域中,以地點形式呈現主題能更貼近使用者在找尋旅遊資訊時的需求,因此透過部落客在文章中所使用的標籤分析部落客所專精的主題,使意見領袖的排名能以主題式呈現。
透過本研究使用者可以藉由以地點呈現主題式的意見領袖排名,導向兼具文章品質、社群影響力以及人氣度的旅遊部落客,透過觀看這些部落客的文章可以更有效率地作出決策。從實驗結果發現以社群影響力衡量意見領袖的效果最佳,其次為人氣度,最終結合所有分數後的排名結果能優於社群影響力,驗證本研究提出的方法能更有效的辨識出部落格中的意見領袖。
英文摘要 Tourism has become an indispensable part of life. There are many online travel related blog articles. Due to massive information, online readers tend to watch their favorite bloggers articles. Popular bloggers are called opinion leaders. Compared to other commentators, opinion leader has high interaction. Their influence could not be ignored.
Popular bloggers are often ranked by popularity, and it does not fully reflect the usefulness of the article. This study analyzes the sentiment and trend of the articles of the bloggers and establishes the influence network by the subscribing relationship. Combining the features above, the opinion leaders ranking will be more in line with expectations. In the field of tourism, adopting location to be topic can be more close to the needs of users. Through the use of blogger defined tag to analyze their expertise, the ranking results can be presented by topic.
Through this study, users can choose target bloggers based on opinion leader ranking results which presented by topic. They could browse these bloggers’ articles to make decision more efficient. The experimental results show that using social influence score to identify opinion leader could get the best result compared with other scores. Finally, this study identified opinion leader by combining all scores in to one. The ranking results could perform better than using social influence score.
論文目次 第1章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 5
1.3 研究範圍與限制 6
1.4 研究流程 6
1.5 論文大綱 7
第2章 文獻探討 8
2.1 部落格 8
2.2 意見領袖 9
2.3 情感分析 11
2.4 鏈結分析 12
2.5 Google Trends 14
2.6 TripAdvisor 15
2.7 廣義知網 16
2.8 大眾分類法 17
2.9 小結 19
第3章 研究方法 20
3.1 研究架構 20
3.2 資料前處理模組 21
3.3 標籤分群模組 23
3.4 社群影響力模組 27
3.5 內文分析模組 28
3.5.1 情感分析 29
3.5.2 趨勢分析 30
3.6 意見領袖辨識模組 32
3.7 小結 35
第4章 系統建置與驗證 36
4.1 系統環境建置 36
4.2 實驗方法 37
4.2.1 資料來源 38
4.2.2 評估指標 39
4.3 參數設定 40
4.4 實驗結果 43
4.4.1 實驗一 43
4.4.2 實驗二 44
4.4.3 實驗三 46
4.4.4 實驗四 48
4.4.5 實驗五 50
第5章 結論與未來方向 52
5.1 研究成果 52
5.2 未來研究方向 54
參考文獻 55
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