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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 莊裕澤(Yuh-Jzer Joung) | |
dc.contributor.author | Ka-U Chao | en |
dc.contributor.author | 周家裕 | zh_TW |
dc.date.accessioned | 2021-06-16T05:28:46Z | - |
dc.date.available | 2014-08-21 | |
dc.date.copyright | 2014-08-21 | |
dc.date.issued | 2014 | |
dc.date.submitted | 2014-08-14 | |
dc.identifier.citation | [1] Daniel A. Keim (2002), Information Visualization and Visual Data Mining, IEEE Transactions on Visualization and Computer Graphics 8, 1-8.
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/56441 | - |
dc.description.abstract | With the progress made in the Web 2.0 technology, people are more likely to share their opinions, status and feelings via social media. But due to the explosion of data in volume on the Internet, people are being overwhelmed by the overloading information and begin to get lost and confused. Since people are used to find and read the online reviews before making their further decisions recently, a tool which is able to summarize the opinion data and reveal the explicit social image of a particular target should be proposed and introduced.
According to the previous work, Ting-Ying Huang has proposed a visual representation which is able to display the overall summarization of targets’ reputations. However, in most situations, people are likely to be interested in a specific aspect of individuals. Therefore, some additional visual approaches should be proposed to gain the meaningful clues. In this thesis, we aim at refining both the reputation evaluation methods and the visual representations which are suggested by Ting-Ying Huang. To accurately estimate the explicit social images of several particular targets, we analyze the opinion data at sentence level by incorporating the knowledge of Natural Language Processing. Additionally, we propose several static visualizations to reveal the detailed information such as the temporal evolutions, topical summarizations, content diversity among various features and social mediums. Moreover, to enhance the graphical perception and comprehension, we create an animated bubble chart which is able to exhibit the trends and changing patterns over time. Furthermore, we offer a fully interactive mean for users to examine and explore the opinion data via any viewing aspects. | en |
dc.description.provenance | Made available in DSpace on 2021-06-16T05:28:46Z (GMT). No. of bitstreams: 1 ntu-103-R99725047-1.pdf: 4003592 bytes, checksum: 635d3bd172d8f4a05c2cb52d030aa7e4 (MD5) Previous issue date: 2014 | en |
dc.description.tableofcontents | 1. Introduction ………………………………………………………………………….... 1
1.1 Backgrounds and Motivations ………………………………………………. 1 1.2 Our Contributions ………………………………………………………….... 3 2. Related Works ……………………………………………………………………….... 4 2.1 The Definitions of Reputation …………………………………………….… 4 2.2 Opinion Analysis and Feature Extraction …………………………………….7 2.2.1 Opinion Analysis ………………………………………………….. 7 2.2.2 Chinese words analysis ………………………………………….… 8 2.2.3 Feature Extraction …………………………………………….…… 9 2.2.4 Brief Summary …………………………………………………… 10 2.3 Information Visualization ………………………………………………….. 11 2.3.1 Textual Data and Document Visualizations ……………………... 12 2.3.2 Temporal Data Visualizations ……………………………………. 16 2.3.3 Visualizations of Social Network ………………………………... 18 2.3.4 Brief Summary …………………………………………………… 23 2.4 Animated Visualization ……………………………………………………. 24 2.4.1 Introduction of Animated Visualization …………………………. 24 2.4.2 The applications of Animated Visualization ……………………... 26 2.4.3 Brief Summary …………………………………………………… 30 3. Methodology ………………………………………………………………………… 31 3.1 Method Overview and Data Pre-processing ……………………………….. 31 3.2 Opinion Analysis Method ………………………………………………..… 33 3.3 Estimations of Reputation and Social Image ………………………………. 35 3.4. Visual Analysis ………………………………………………………….… 37 3.4.1 To Display the Overall Summarization ………………………..… 37 3.4.2 Animated Visualization ………………………………………..… 38 3.4.3 To Display the Temporal Information …………………………… 40 3.4.3.1 To Display the Temporal Hierarchical Structures …...… 40 3.4.3.2 Using Timeline to Display the Evolutions …………...… 41 3.4.4 Textual Data Summarization …………………………………….. 43 3.4.5 Variations among Different Mediums …………………................ 44 3.4.6 Content Diversity among Various Features …………………….... 45 3.4.7 Interactive Force Bubble Chart …………………………………... 46 3.5 Summary ………………………………………………………………….... 48 4. Results and Discussions ……………………………………………………………... 49 4.1 Experimental Data …………………………………………………………. 49 4.2 Experiments ………………………………………………………………... 50 4.2.1 Case 1: Cell Phones …………………………………………....… 50 4.2.2 Case 2: Movies ………………………………………………...…. 67 4.3 User Interviews …………………………………………………………..… 81 5. Conclusions ……………………………………………………………….…………. 85 5.1 Conclusions ………………………………………………………………… 85 5.2 Suggestions and Limitations ……………………………………………..… 86 References ……………………………………………………………………………...… 89 | |
dc.language.iso | en | |
dc.title | 利用靜態、動態和互動視覺化技術去呈現網上評價 | zh_TW |
dc.title | Visualizing the online reputations of particular targets via static, animated and interactive visual techniques | en |
dc.type | Thesis | |
dc.date.schoolyear | 102-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 楊立偉(Li-Wei Yang),陳炳宇(Bing-Yu Chen),盧信銘(Hsin-Min Lu) | |
dc.subject.keyword | 評價,意見分析,資訊視覺化,動畫, | zh_TW |
dc.subject.keyword | reputation,opinion analysis,information visualization,animation, | en |
dc.relation.page | 45 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2014-08-14 | |
dc.contributor.author-college | 管理學院 | zh_TW |
dc.contributor.author-dept | 資訊管理學研究所 | zh_TW |
顯示於系所單位: | 資訊管理學系 |
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