淡江大學覺生紀念圖書館 (TKU Library)
進階搜尋


系統識別號 U0002-0109201415131000
中文論文名稱 利用中文意見探勘系統應用於電信公司口碑比較之研究
英文論文名稱 Research of Compare Telecom Marketing by Using Chinese Opinion Mining System
校院名稱 淡江大學
系所名稱(中) 資訊工程學系碩士在職專班
系所名稱(英) Department of Computer Science and Information Engineering
學年度 102
學期 2
出版年 103
研究生中文姓名 林炳志
研究生英文姓名 Pin-Chih Lin
學號 701410283
學位類別 碩士
語文別 中文
第二語文別 英文
口試日期 2014-06-20
論文頁數 108頁
口試委員 指導教授-蔣璿東
委員-葛煥昭
委員-王鄭慈
委員-蔣璿東
中文關鍵字 意見探勘  口碑分析 
英文關鍵字 Opinion Mining  MouthMarketing 
學科別分類 學科別應用科學資訊工程
中文摘要 隨著3G網路通訊進入4G網路通訊時代的來臨,在第三類行動通訊用戶從2011年03月1934萬戶至2014年03月增加到2543萬戶,三年總共成長609萬戶。也隨著電信的行動上網品質與手機多元化功能服務的提升,消費者對於通訊品質就變成非常注的看重。因此台灣各大電信業者不斷提升服務來吸引換合約的消費者。使用者的過往經驗已成為消費者參考指標之ㄧ,而資訊都皆可在網路上的各大討論平台獲取,例如:個人部落格、PTT、網路論壇等等。在未來服務品質口碑的維護與改善,將成為電信業者重視的一環。現在消費者遇到查詢口碑時候就非常耗時間與體力,因為網路上參考資訊量是非常龐大。消費者在人工模式要從龐大的資料中找尋,來判斷所有資料是否需要,不僅非常費工也會找到太多不具有參考價值的評論資訊。為了提高效率電信業者在消費者對口碑的評價反應之後,在未來的上網速度、服務品質、收訊品質、價格等四大面是否有更近一步的改善。本研究是以長時間追蹤方式,並以先前系統分析的文章結果做比較,而先前研究結果是從Mobile01論壇擷取前系統分析2011年11月至2013年02月共16個月資料(許喬安,2013),與此次2013年3月至2014年04月共14個月電信評論的內容擷取,探討研究與之結果判定電信公司對於品質,是否有持續提供更完善服務的改善。
英文摘要 Bringing 3G into the 4G network communications era, the third-category mobile telecommunication users increased from 19.34 million in March 2011 to 254.3 million in March 2014, a total increase of 6.09 million in 3 years. With the improved mobile Internet quality and diversified features of mobile phones, consumers now highly value telecommunications quality. Hence, major telecommunications operators continue to upgrade services to attract contract renewal consumers. Past experiences of users have become one of the consumers’ reference indicators, while information is available in major discussion platforms, such as personal blogs, PTT, Internet forums, and so on. In the future, the maintenance and improvement of service quality word-of-mouth will become an important part valued by telecommunications operators. Consumers’ word-of-mouth queries are time-consuming and laborious because the Internet has a very large amount of reference information. Consumers must manually search from the extensive data to determine whether information is needed. It is not only laborious, but also lacks comment information that has reference value. In order to enhance efficiency, telecommunications operators that react to consumers’ word-of-mouth ratings should further make improvement in four dimensions: Internet speed, service quality, reception quality, and price. This study was conducted through long-term tracking and compared articles pertaining to analysis of previous systems. As for the previous research results, Mobile01 Forum was used to extract analysis of previous systems. A total of 16 data entries from November 2011 to February 2013 and 14 entries of communications comment contents from March 2013 to April 2014 were extracted to discuss the research results and determine whether telecommunications companies continued to make improvement in order to provide more comprehensive services.
論文目次 目錄
第1章 緒論 1
1.1 研究動機與目的 1
1.2 研究架構 4
第2章 文獻探討 5
2.1 意見單元定義 5
2.2 意見探勘系統 8
2.2.1 英文意見探勘系統 8
2.2.2 中文意見探勘系統 15
2.3 口碑行銷與網路口碑 17
第3章 研究方法 19
3.1 系統設計 19
3.1.1 自動排程設定 20
3.1.2 監控規格設定 21
3.1.3 負面文章分析介面 24
3.1.4 報表分析設定 28
3.2 意見元素新增管理介面 36
3.2.1 「意見詞標記」演算法 36
3.2.2 「斷詞斷字」演算法 38
3.2.3 「OP+OP」演算 40
3.2.4 「OP不OP」演算法 41
3.2.5 「OP+"了"」演算法 41
3.2.6 「OP+名詞」演算法 42
第4章 實驗結果與分析 44
4.1 電信分析 44
4.1.1 電信分析四大面向 44
4.1.2 五大電信業者整體比較 45
4.2 電信分析四大面向 54
4.2.1 面向一:上網速度探討 54
4.2.2 面向二:收訊品質探討 62
4.2.3 面向三:服務品質探討 66
4.2.4 面向四:價格的探討 71
4.3 異常評價分析 77
第5章 結論 87
參考文獻 89
附錄A 英文論文 94

圖目錄
圖1 Opinion Observer的比較畫面 9
圖2 人工標註系統畫面 10
圖3 WebFountain GUI經過意見分析後的產品比較圖 11
圖4 WebFountain可以讓使用者選擇產品以及來源 11
圖5 ReMiner在手機上根據特徵分類(Common圖) 12
圖6 Special圖 13
圖7 Cloud圖 14
圖8 Categories圖 14
圖9 CopeOpi使用者選擇畫面 16
圖10 各個時間趨勢 16
圖11 包含主題的文章 16
圖12 可選擇有關的電影以及特徵,並且知道正負傾向評論等級 17
圖13 系統功能介面 19
圖14 自動排程設定圖 20
圖15 排程時間設定圖 21
圖16 文章自動更新作業記錄查詢介面 21
圖17 監控規格設定主介面圖 21
圖18 監控規格設定條件介面圖 22
圖19 監控規格新增介面圖 23
圖20 監控規格條件選擇介面圖 23
圖21 監控結果查詢主介面圖 25
圖22 監控結果查詢明細資料介面圖 26
圖23 瀏覽文章介面圖 26
圖24 負面文章查詢主介面圖 27
圖25 負面文章發文者查詢主介面圖 28
圖26 Topic分析介面圖 29
圖27 Topic分析種類選擇圖 30
圖28 Topic分析選擇Topic圖 30
圖29 Topic分析選擇資料區間圖 31
圖30 Topic分析結果圖 31
圖31 Feature/產品分析介面圖 32
圖32 Feature/產品分析選擇Feature介面圖 33
圖33 Feature/產品分析結果圖 33
圖34 異常評價分析介面圖 34
圖35 異常評價分析結果圖 34
圖36 雷達圖分析介面圖 35
圖37 雷達圖分析結果圖 36
圖38 「意見詞標記」演算法編輯介面圖 37
圖39 意見詞與Feature關聯編輯介面圖 38
圖40 斷詞斷字找OP/N介面圖 39
圖41 意見詞(或名詞)與Feature對應關係編輯介面圖 39
圖42 OP+OP結果編輯介面圖 40
圖43 OP+"了"編輯介面圖 42
圖44 OP+名詞編輯介面圖 42
圖45 意見元素新增管理執行完畢訊息圖 43
圖46 五大電信業者討論文章數及比例2011-11~2013-02 46
圖47 五大電信業者討論文章數及比例2013-03~2014-04 46
圖48 五大業者文章評價分析折線圖2011-11~2013-02 48
圖49 五大業者文章評價分析折線圖2013-03~2014-04 48
圖50 五大業者文章評價分析折線圖(更改後)2011-11~2013-02 53
圖51 中華、遠傳、台灣大哥大【上網速度】文章評價分析2011-11~2013-02 57
圖52 中華、遠傳、台灣大哥大【上網速度】文章評價分析2013-03~2014-04 57
圖53 中華、遠傳、台灣大哥大【收訊品質】文章評價分析2011-11~2013-02 63
圖54 中華、遠傳、台灣大哥大【收訊品質】文章評價分析2013-03~2014-04 64
圖55 中華、遠傳、台灣大哥大【服務品質】文章評價分析2011-11~2013-02 68
圖56 中華、遠傳、台灣大哥大【服務品質】文章評價分析2013-03~2014-04 69
圖57 NCC查詢各大業者費率資料圖 72
圖58 中華、遠傳、台灣大哥大【價格】文章評價分析2011-11~2013-02 74
圖59 中華、遠傳、台灣大哥大【價格】文章評價分析2013-03~2014-04 74
圖60 三星相關討論文章暴衝圖(資料來源:0pView研究團隊) 80
圖61 網路寫手提供Samsung三星【Note 2】手機厚度圖(資料來源:Mobile01網站資料) 81
圖62 網路寫手提供HTC宏達電【DNA】手機厚度圖(資料來源:Mobile01網站資料) 81
圖63 收訊品質異常分析(直線圖) 2013年04月 83
圖64 收訊品質異常分析(直線圖) 2013年05月 83
圖65 收訊品質異常分析(直線圖) 2013年06月 84
圖66 收訊品質異常分析(直線圖) 2013年07月 84

表目錄
表 1 意見元素 6
表 2 評估方式 45
表 3 五大電信業者討論文章總數 46
表 4 亞太2012年06月正面評價 49
表 5 遠傳2012年02月負面評價 50
表 6 遠傳2013年10月正面評價 51
表 7 亞太2013年10月負面評價 52
表 8 五大業者評價最高與最低分析 53
表 9 中華電信2012年06月上網速度【正面】評價 58
表 10 遠傳電信2012年05月上網速度【負面】評價 59
表 11 遠傳電信2013年10月上網速度【正面】評價 60
表 12 中華、台灣大2013年12月、2014年月 上網速度【負面】評價 61
表 13 遠傳電信上網速度評價分析 61
表 14 遠傳電信2012年06月【收訊品質】正面評價 64
表 15 中華電信2012年02月【收訊品質】負面評價 65
表 16 中華電信2013年11月【收訊品質】正面評價 65
表 17 台灣大哥大2013年08月【收訊品質】負面評價 66
表 18 中華、遠傳電信2012年06月【服務品質】正面評價 69
表 19 中華電信2012年07月【服務品質】負面評價 70
表 20 遠傳電信2013年08月【服務品質】正面評價 70
表 21 中華、遠傳電信2013年09、12月【服務品質】負面評價 71
表 22 中華、遠傳電信2013年01月【價格】正面評價 75
表 23 中華電信2012年07月【價格】負面評價 75
表 24 中華電信2013年12月【價格】正面評價 76
表 25 台灣大哥大2013年04月【價格】負面評價 77
表 26 費率評價最高表 77
表 27 網路寫手工作回報表(資料來源:Mobile01網友提供鵬泰公司內部資料) 79
表 28 ID:seanastin2013年05與2013年07發表評論表 85
參考文獻 [1] P. D. Turney, "Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews," presented at the Proceedings of the 40th Annual Meeting on Association for Computational Linguistics, Philadelphia, Pennsylvania, 2002.
[2] M. Hu and B. Liu, "Mining and summarizing customer reviews," presented at the Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining, Seattle, WA, USA, 2004.
[3] L.-W. Ku and H.-H. Chen, "Mining opinions from the Web: Beyond relevance retrieval," Journal of the American Society for Information Science and Technology, vol. 58, pp. 1838-1850, 2007.
[4] N. Kobayashi, K. Inui, and Y. Matsumoto, "Opinion Mining from Web Documents: Extraction and Structurization," Information and Media Technologies, vol. 2, pp. 326-337, 2007.
[5] S.-M. Kim and E. Hovy, "Determining the sentiment of opinions," presented at the Proceedings of the 20th international conference on Computational Linguistics, Geneva, Switzerland, 2004.
[6] B. Liu and L. Zhang, "A Survey of Opinion Mining and Sentiment Analysis
Mining Text Data," C. C. Aggarwal and C. Zhai, Eds., ed: Springer US, 2012, pp. 415-463.
[7] B. Liu, M. Hu, and J. Cheng, "Opinion observer: analyzing and comparing opinions on the Web," presented at the Proceedings of the 14th international conference on World Wide Web, Chiba, Japan, 2005.
[8] G. A. Miller. (1980). WordNet. Available: http://wordnet.princeton.edu/
[9] P. J. Stone, D. C. Dunphy, and M. S. Smith, "The General Inquirer: A Computer Approach to Content Analysis," 1966.
[10] A. Esuli and F. Sebastiani, "Sentiwordnet: A publicly available lexical resource for opinion mining," 2006, pp. 417-422.
[11] B. Ohana and B. Tierney, "Sentiment classification of reviews using SentiWordNet," in 9th. IT & T Conference, 2009, p. 13.
[12] General Inquire. Available: http://www.wjh.harvard.edu/~inquirer/
[13] A. Esuli and F. Sebastiani, "Determining term subjectivity and term orientation for opinion mining," 2006, pp. 193-200.
[14] A. Andreevskaia and S. Bergler, "Mining WordNet for fuzzy sentiment: Sentiment tag extraction from WordNet glosses," 2006, pp. 209-216.
[15] L. Zhuang, F. Jing, and X.-Y. Zhu, "Movie review mining and summarization," presented at the Proceedings of the 15th ACM international conference on Information and knowledge management, Arlington, Virginia, USA, 2006.
[16] 董振東, "HowNet," 1999
[17] T. Peiliang, L. Yuanchao, L. Ming, and Z. Shanzong, "Research of Product Ranking Technology Based on Opinion Mining," in Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on, 2009, pp. 239-243.
[18] S. Bin and C. Kuiyu, "Mining Chinese Reviews," in Data Mining Workshops, 2006. ICDM Workshops 2006. Sixth IEEE International Conference on, 2006, pp. 585-589.
[19] 杨锋, 彭勤科, and 徐涛, "基于随机网络的在线评论情绪倾向性分类," 自动化学报, vol. 36, pp. 837-844, 2010.
[20] 李林琳, "基于特定领域的汉语句子意见挖掘," 上海交通大学, 2008.
[21] 娄德成 and 姚天昉, "汉语句子语义极性分析和观点抽取方法的研究," 计算机应用, vol. 26, pp. 2622-2625, 2006.
[22] L.-W. Ku, H.-W. Ho, and H.-H. Chen, "Opinion mining and relationship discovery using CopeOpi opinion analysis system," Journal of the American Society for Information Science and Technology, vol. 60, pp. 1486-1503, 2009.
[23] 陳立, "中文情感語意自動分類之研究," 2010.
[24] 楊盛帆, "以整合式規則來做網路論壇上的 3C 產品口碑分析," 元智大學資訊管理學系研究所碩士論文, 2009.
[25] 孫瑛澤, 陳建良, 劉峻杰, 劉昭麟, and 蘇豐文, "中文短句之情緒分類," 2010.
[26] 謝鎮宇, "意見探勘在中文評鑑語料之應用," 交通大學資訊學院碩士在職專班資訊組學位論文, 交通大學, 2010.
[27] H. Xu, K. Zhao, L. Qiu, and C. Hu, "Expanding Chinese sentiment dictionaries from large scale unlabeled corpus," 2011.
[28] S. Tan, Y. Wang, and X. Cheng, "Combining learn-based and lexicon-based techniques for sentiment detection without using labeled examples," presented at the Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, Singapore, Singapore, 2008.
[29] P. Turney and M. L. Littman, "Measuring praise and criticism: Inference of semantic orientation from association," 2003.
[30] H. Kanayama and T. Nasukawa, "Fully automatic lexicon expansion for domain-oriented sentiment analysis," presented at the Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing, Sydney, Australia, 2006.
[31] G. Qiu, B. Liu, J. Bu, and C. Chen, "Expanding domain sentiment lexicon through double propagation," 2009, pp. 1199-1204.
[32] G. Qiu, B. Liu, J. Bu, and C. Chen, "Opinion Word Expansion and Target Extraction through Double Propagation," Computational Linguistics, vol. 37, pp. 9-27, 2011/03/01 2011.
[33] A.-M. Popescu and O. Etzioni, "Extracting product features and opinions from reviews," presented at the Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing, Vancouver, British Columbia, Canada, 2005.
[34] Q. Mei, X. Ling, M. Wondra, H. Su, and C. Zhai, "Topic sentiment mixture: modeling facets and opinions in weblogs," presented at the Proceedings of the 16th international conference on World Wide Web, Banff, Alberta, Canada, 2007.
[35] Z. Zhai, B. Liu, L. Zhang, H. Xu, and P. Jia, "Identifying evaluative sentences in online discussions," 2011.
[36] N. Kobayashi, K. Inui, Y. Matsumoto, K. Tateishi, and T. Fukushima, "Collecting Evaluative Expressions for Opinion Extraction
Natural Language Processing – IJCNLP 2004." vol. 3248, K.-Y. Su, J. i. Tsujii, J.-H. Lee, and O. Kwong, Eds., ed: Springer Berlin / Heidelberg, 2005, pp. 596-605.
[37] M. Fuketa, Y. Kadoya, E. Atlam, T. Kunikata, K. Morita, S. Kashiji, et al., "A method of extracting and evaluating good and bad reputations for natural language expressions," International Journal of Information Technology & Decision Making, vol. 4, pp. 177-196, 2005.
[38] A. Esuli and F. Sebastiani, "Determining the semantic orientation of terms through gloss classification," presented at the Proceedings of the 14th ACM international conference on Information and knowledge management, Bremen, Germany, 2005.
[39] C. Zhang, D. Zeng, J. Li, F.-Y. Wang, and W. Zuo, "Sentiment analysis of Chinese documents: From sentence to document level," J. Am. Soc. Inf. Sci. Technol., vol. 60, pp. 2474-2487, 2009.
[40] L. Zhuang, F. Jing, and X. Y. Zhu, "Movie review mining and summarization," 2006, pp. 43-50.
[41] 邱鴻達, "意見探勘在中文電影評論之應用," 國立交通大學 資訊科學與工程研究所, 2011.
[42] 梅家駒等編著, 同義詞詞林, 1983.
[43] X. Ding, B. Liu, and P. S. Yu, "A holistic lexicon-based approach to opinion mining," 2008, pp. 231-240.
[44] Q. Su, X. Xu, H. Guo, Z. Guo, X. Wu, X. Zhang, et al., "Hidden sentiment association in chinese web opinion mining," presented at the Proceedings of the 17th international conference on World Wide Web, Beijing, China, 2008.
[45] V. Hatzivassiloglou and K. R. McKeown, "Predicting the semantic orientation of adjectives," 1997, pp. 174-181.
[46] Y. Qiang, S. Wen, and L. Yijun, "Sentiment Classification for Movie Reviews in Chinese by Improved Semantic Oriented Approach," in System Sciences, 2006. HICSS '06. Proceedings of the 39th Annual Hawaii International Conference on, 2006, pp. 53b-53b.
[47] L. W. Ku, I. C. Liu, C. Y. Lee, K. Chen, and H. H. Chen, "Sentence-Level Opinion Analysis by CopeOpi in NTCIR-7," 2008.
[48] P. Ting-Chun and S. Chia-Chun, "Using Chinese part-of-speech patterns for sentiment phrase identification and opinion extraction in user generated reviews," in Digital Information Management (ICDIM), 2010 Fifth International Conference on, 2010, pp. 120-127.
[49] K. Dave, S. Lawrence, and D. M. Pennock, "Mining the peanut gallery: opinion extraction and semantic classification of product reviews," presented at the Proceedings of the 12th international conference on World Wide Web, Budapest, Hungary, 2003.
[50] M. Gamon, A. Aue, S. Corston-Oliver, and E. Ringger, "Pulse: Mining Customer Opinions from Free Text
Advances in Intelligent Data Analysis VI." vol. 3646, A. Famili, J. Kok, J. Pena, A. Siebes, and A. Feelders, Eds., ed: Springer Berlin / Heidelberg, 2005, pp. 741-741.
[51] T. Wilson, P. Hoffmann, S. Somasundaran, J. Kessler, J. Wiebe, Y. Choi, et al., "OpinionFinder: a system for subjectivity analysis," presented at the Proceedings of HLT/EMNLP on Interactive Demonstrations, Vancouver, British Columbia, Canada, 2005.
[52] J. Huang, O. Etzioni, L. Zettlemoyer, K. Clark, and C. Lee, "RevMiner: an extractive interface for navigating reviews on a smartphone," presented at the Proceedings of the 25th annual ACM symposium on User interface software and technology, Cambridge, Massachusetts, USA, 2012.
[53] J. Yi and W. Niblack, "Sentiment mining in WebFountain," in Data Engineering, 2005. ICDE 2005. Proceedings. 21st International Conference on, 2005, pp. 1073-1083.
[54] L. Chien-Liang, H. Wen-Hoar, L. Chia-Hoang, L. Gen-Chi, and E. Jou, "Movie Rating and Review Summarization in Mobile Environment," Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, vol. 42, pp. 397-407, 2012.
論文使用權限
  • 同意紙本無償授權給館內讀者為學術之目的重製使用,於2019-09-02公開。
  • 同意授權瀏覽/列印電子全文服務,於2019-09-02起公開。


  • 若您有任何疑問,請與我們聯絡!
    圖書館: 請來電 (02)2621-5656 轉 2281 或 來信