請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/47355完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 林守德 | |
| dc.contributor.author | Chien-Tung Ho | en |
| dc.contributor.author | 何建彤 | zh_TW |
| dc.date.accessioned | 2021-06-15T05:56:16Z | - |
| dc.date.available | 2010-08-20 | |
| dc.date.copyright | 2010-08-20 | |
| dc.date.issued | 2010 | |
| dc.date.submitted | 2010-08-17 | |
| dc.identifier.citation | [1] Micro-blogging : http://en.wikipedia.org/wiki/Microblogging
[2] Tumblr : http://www.tumblr.com/ [3] Twitter : http://twitter.com/ [4] Viral Marketing : http://en.wikipedia.org/wiki/Viral_marketing [5] M. Richardson and P. Domingos. Mining knowledge-sharing sites for viral marketing. In Proc. of the 8th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining [6] D. Kempe, J. M. Kleinberg, and ′E. Tardos. Maximizing the spread of influence through a social network. In Proc. of the 9th ACM Int. Conf. on Knowledge Discovery and Data Mining [7] Gruhl, D., Guha, R., Liben-Nowell, D., and Tomkins, A. Information diffusion through blogspace. In Proceedings of the 13th international Conference on World Wide Web. WWW '04. [8] J. Leskovec, A. Krause, C. Guestrin, C. Faloutsos, J. VanBriesen, and N. S. Glance. Cost-effective outbreak detection in networks. In Proc. of the 13th ACM Int. Conf. on Knowledge Discovery and Data Mining KDD’07. [9] Sun, E., Rosenn, I., Marlow, C. and Lento, T. 2009. Gesundheit! Modeling Contagion through Facebook News Feed. Association for the Advancement of artificial Intelligence. [10] Kwak, H., Lee, C., Park, H., and Moon, S. 2010. What is Twitter, a social network or a news media?. In Proceedings of the 19th international Conference on World Wide Web. WWW '10. [11] 噗浪流行排行榜：http://www.gururu.tw/噗浪的流行排行.html [12] Plurk訊息量統計: http://wiselysong.blogspot.com/2009/12/2009-12-21-plurk.html [13] Open Flash Chart : http://teethgrinder.co.uk/open-flash-chart/ [14] Simile-widgets : http://www.simile-widgets.org/timeline/ [15]GraphGear : http://www.creativesynthesis.net/recycling/graphgeardemo/ [16] Xiaodan Song, Yun Chi, Koji Hino, Belle L. Tseng: Information flow modeling based on diffusion rate for prediction and ranking. WWW '07 [17] Cha, M., Mislove, A., and Gummadi, K. P. 2009. A measurement-driven analysis of information propagation in the flickr social network. In Proceedings of the 18th international Conference on World Wide Web. WWW '09. [18] Goyal, A., Bonchi, F., and Lakshmanan, L. V. 2010. Learning influence probabilities in social networks. In Proceedings of the Third ACM international Conference on Web Search and Data Mining. WSDM '10. ACM [19] Sakaki, T., Okazaki, M., and Matsuo, Y. 2010. Earthquake shakes Twitter users: real-time event detection by social sensors. In Proceedings of the 19th international Conference on World Wide Web. WWW '10. ACM | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/47355 | - |
| dc.description.abstract | 微網誌是一種新型的社群網路應用服務，近來吸引越來越多的使用者加入。在微
網誌上，使用者透過張貼特殊的事件、對周遭人事物的感覺想法、甚至有趣的資 訊於個人頁面，進而達到與身旁親朋好友甚至世界上不認識的人交換資訊、相互 討論、分享經驗的目地。本論文的主旨在定義一套測量微網誌上資訊傳播的能力 的方法主要針對下列三個問題深入研究： 1. 如何定義以及有效的量化一項話題在微網誌上傳播的程度與速度？ 2. 如何判斷一項話題傳播是經由微網誌內部傳播還是透過外部影響？ 3. 如何設計一套系統能夠描述並視覺化在微網誌上的資訊傳播？ 我們提出了一套有效的測量方法，將每位使用者對於話題的傳播能力排名，其測 量的方法主要考慮三個面向：(a) 能夠吸引參與話題的人數，(b) 將資訊傳播出去 的速度，(c) 地理位置上的傳播範圍。此外，除了根據上述三面向來建立傳播模型， 我們同時利用話題提供者數目和參與者數目的比例，判斷資訊的傳播是透過內部 散播還是受到外部媒體的影響。最終我們將設計的方法實際運用在微網誌Plurk 上 來進行驗證和分析，並實做一資訊傳播的視覺化系統，以呈現特定主題於微網誌 之傳播現象。 | zh_TW |
| dc.description.abstract | Micro-blog is a kind of social network web service and has become more and more popular in daily life. In micro-blog, bloggers can exchange information and discuss ideas with each other, and share experience with friends or even strangers. This paper aims at identifying a measurement for information propagation in micro-blogs and answer the following questions:
1. How to quantify a person’s capability to distribute certain idea in a micro-blog? 2. How to measure the level of propagation of a concept in a micro-blog? 3. How to determine whether certain idea is propagated internally in a micro-blog? We propose methods to effectively measure the capability of the information propagation for each user in micro-blogs. The measurement focuses on three aspects: (a) the number of influenced people, (b) the speed of propagation, and (c) the geographic distance of propagation. Besides, we also propose a method to identify whether a topic is propagated inside the micro-blog or based on outer media (e.g. news). In the end, we construct a online system that allows us to perform some experiments to visualize the propagation paths, influence scores, and geographical information among people with respect to the user-given terms. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T05:56:16Z (GMT). No. of bitstreams: 1 ntu-99-R97944013-1.pdf: 1900234 bytes, checksum: fd1b4eae416bde19c283ae3be90be742 (MD5) Previous issue date: 2010 | en |
| dc.description.tableofcontents | Acknowledgements I
摘要 II Abstract III Table of Contents V List of Figures VII List of Table VIII Appendix IX 1. Introduction 1 1.1 Background 1 1.2 Purpose and Motivations 3 1.3 Methodology Outline 3 1.4 Contributions 4 1.5 Paper Organization 5 2. Methodology 6 2.1 Model Overview 7 2.2 Tree Set Construction 8 2.3 Scoring on Influenced Trees 14 2.3.1 Influenced Score 15 2.3.2 Speed of Propagation 15 2.3.3 Distance Score 17 2.4 Term Score 19 2.5 Internal or External Propagation 20 3. Experiment on Plurk 23 3.1 Plurk Data 23 3.1.1 History 23 3.1.2 Characteristic 24 3.2 Experiment 25 3.2.1 The ranking of persons based on terms 25 3.2.2 Internal or External 28 4. System Demo and Visualization 29 4.1 System Architecture 29 4.2 Case Study 31 4.2.1 Global Information 32 4.2.2 Local Information 36 5. Related Works 42 5.1 Model-based Information Diffusion 42 5.2 Propagation of Real Data 43 5.3 Applications of Information Propagation 44 6. Conclusion 46 6.1 Summary of Contributions 46 6.2 Future Work 47 7. Reference 48 | |
| dc.language.iso | zh-TW | |
| dc.subject | 視覺化 | zh_TW |
| dc.subject | 資訊傳播 | zh_TW |
| dc.subject | 模型 | zh_TW |
| dc.subject | 社群網路 | zh_TW |
| dc.subject | model | en |
| dc.subject | visualization | en |
| dc.subject | social network | en |
| dc.subject | information propagation | en |
| dc.title | 基於微網誌平台之資訊傳播模型與視覺化 | zh_TW |
| dc.title | Modeling and Visualizing Information Propagation in Micro-Blogging Platform | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 98-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 廖婉君,許永真,周承復 | |
| dc.subject.keyword | 資訊傳播,社群網路,模型,視覺化, | zh_TW |
| dc.subject.keyword | information propagation,social network,model,visualization, | en |
| dc.relation.page | 51 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2010-08-18 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊網路與多媒體研究所 | zh_TW |
| 顯示於系所單位： | 資訊網路與多媒體研究所 | |
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