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題名 針對社群媒體上的趨勢變化之視覺化探索工具
A study of visual exploration tool for comparing trend作者 郭建凱
Kuo, Jian-Kai貢獻者 紀明德
Chi, Ming-Te
郭建凱
Kuo, Jian-Kai關鍵詞 資料視覺化
多維度資料
時序性資料
社群網路日期 2017 上傳時間 3-Jan-2018 16:20:31 (UTC+8) 摘要 隨著社群媒體的普及，新聞媒體與意見領袖逐漸重視在社群媒體上以貼文方式發佈新聞資訊，社群媒體成為許多使用者會接收新聞與重大事件的主要管道且透過社群媒體的評論、分享與按讚等互動機制表達立場，這些即時互動行為是傳統媒體缺乏的機制，如何分析也是研究上的挑戰。本研究將針對Facebook上的貼文與互動行為進行分析，提供一款互動視覺化系統，找出貼文資料集中相似的貼文群集以及隨著時間推移下貼文屬性的變化，進一步瞭解Facebook上使用者、貼文與重大事件之間的相互影響。由於Facebook上的貼文與互動行為具多維度屬性，我們透過降維演算法將大量的貼文以二維散佈圖呈現，達到將相似貼文分群的效果。另外，我們設計了一種視覺化呈現方法，「Time Block」，突顯出時間的推移下貼文屬性的變化，藉此觀察出貼文資料集是否存在特定的模式。最後提供即時互動的操作介面，以及貼文屬性以及關鍵字兩者的統計，藉此連接到貼文集的屬性與時間的分佈關係，協助以視覺化方式進行探索與分析。最後，透過案例分析與使用者測試呈現此視覺化探索工具的優缺點。
Social media becomes an essential medium for broadcast news. News media and option leader post information and people love to receive news and interactive using comment and likes to feedback. It is a research challenge to analysis this massive amount interactive behavior data in social media. In this paper, we propose an interactive visualization system to explore on the posts and interactions on Facebook. This system can help a user to find out the similar interactive behavior cluster and the trend of time-varying attributes to understand how the users, posts, and a big event to affect each other. Facebook Posts and interactive behavior contains multiple dimensional attributes; we adopt the dimensional reduce algorithm and 2D scatter plot to present the cluster in the spatial domain. Then, we design a time-varying visualization method, "Time Block,` can highlight the changing attributes and observe the unique pattern in the time domain. Also, we design a real-time interactive interface to connect the cluster and trend visualization with additional keyword distribution and attribute statistics. Finally, we use case study and user study to demonstrate the advantage of the proposed system.參考文獻 [1]B. Bach, N. Henry‐Riche, T. Dwyer, T. Madhyastha, J. D. Fekete, and T. Grabowski, "Small MultiPiles: Piling time to explore temporal patterns in dynamic networks," in Computer Graphics Forum, 2015, vol. 34, no. 3, pp. 31-40: Wiley Online Library.[2]B. Bach, C. Shi, N. Heulot, T. Madhyastha, T. Grabowski, and P. Dragicevic, "Time curves: Folding time to visualize patterns of temporal evolution in data," IEEE transactions on visualization and computer graphics, vol. 22, no. 1, pp. 559-568, 2016. [3]R. Blanch, R. Dautriche, and G. Bisson, "Dendrogramix: A hybrid tree-matrix visualization technique to support interactive exploration of dendrograms," in Visualization Symposium (PacificVis), 2015 IEEE Pacific, 2015, pp. 31-38: IEEE.[4]N. Cao, C. Shi, S. Lin, J. Lu, Y.-R. Lin, and C.-Y. Lin, "TargetVue: Visual analysis of anomalous user behaviors in online communication systems," IEEE transactions on visualization and computer graphics, vol. 22, no. 1, pp. 280-289, 2016.[5]J. Chen, A. M. MacEachren, and D. J. Peuquet, "Constructing overview+ detail dendrogram-matrix views," IEEE transactions on visualization and computer graphics, vol. 15, no. 6, pp. 889-896, 2009.[6]Q. Cui, M. O. Ward, and E. A. Rundensteiner, "Enhancing scatterplot matrices for data with ordering or spatial attributes," in Electronic Imaging 2006, 2006, pp. 60600R-60600R-11: International Society for Optics and Photonics.[7]M. Hu, K. Wongsuphasawat, and J. Stasko, "Visualizing Social Media Content with SentenTree," IEEE Transactions on Visualization and Computer Graphics, vol. 23, no. 1, pp. 621-630, 2017.[8]M. Kim, K. Kang, D. Park, J. Choo, and N. Elmqvist, "Topiclens: Efficient multi-level visual topic exploration of large-scale document collections," IEEE Transactions on Visualization and Computer Graphics, vol. 23, no. 1, pp. 151-160, 2017.[9]B. Kondo and C. Collins, "Dimpvis: Exploring time-varying information visualizations by direct manipulation," IEEE transactions on visualization and computer graphics, vol. 20, no. 12, pp. 2003-2012, 2014.[10]L. v. d. Maaten and G. Hinton, "Visualizing data using t-SNE," Journal of Machine Learning Research, vol. 9, no. Nov, pp. 2579-2605, 2008.[11]S. Rufiange and M. J. McGuffin, "DiffAni: Visualizing dynamic graphs with a hybrid of difference maps and animation," IEEE Transactions on Visualization and Computer Graphics, vol. 19, no. 12, pp. 2556-2565, 2013.[12]J. Stasko, R. Catrambone, M. Guzdial, and K. McDonald, "An evaluation of space-filling information visualizations for depicting hierarchical structures," International journal of human-computer studies, vol. 53, no. 5, pp. 663-694, 2000.[13]J. Stasko and E. Zhang, "Focus+ context display and navigation techniques for enhancing radial, space-filling hierarchy visualizations," in Information Visualization, 2000. InfoVis 2000. IEEE Symposium on, 2000, pp. 57-65: IEEE.[14]F. Viégas et al., "Google+ ripples: A native visualization of information flow," in Proceedings of the 22nd international conference on World Wide Web, 2013, pp. 1389-1398: ACM.[15]M. Wattenberg, F. Viégas, and I. Johnson, "How to Use t-SNE Effectively," Distill, vol. 1, no. 10, p. e2, 2016.[16]F. Wickelmaier, "An introduction to MDS," Sound Quality Research Unit, Aalborg University, Denmark, vol. 46, 2003.[17]X. Yuan, D. Ren, Z. Wang, and C. Guo, "Dimension projection matrix/tree: Interactive subspace visual exploration and analysis of high dimensional data," IEEE Transactions on Visualization and Computer Graphics, vol. 19, no. 12, pp. 2625-2633, 2013.[18]F. Zhou et al., "Dimension reconstruction for visual exploration of subspace clusters in high-dimensional data," in Pacific Visualization Symposium (PacificVis), 2016 IEEE, 2016, pp. 128-135: IEEE.[19]MUNZNER, Tamara. Visualization analysis and design. CRC press, 2014.[20]https://developers.facebook.com/docs/graph-api/advanced/rate-limiting[21]https://github.com/yanyiwu/nodejieba/blob/master/README_EN.md 描述 碩士
國立政治大學
資訊科學學系
104753026資料來源 http://thesis.lib.nccu.edu.tw/record/#G0104753026 資料類型 thesis dc.contributor.advisor 紀明德 zh_TW dc.contributor.advisor Chi, Ming-Te en_US dc.contributor.author (Authors) 郭建凱 zh_TW dc.contributor.author (Authors) Kuo, Jian-Kai en_US dc.creator (作者) 郭建凱 zh_TW dc.creator (作者) Kuo, Jian-Kai en_US dc.date (日期) 2017 en_US dc.date.accessioned 3-Jan-2018 16:20:31 (UTC+8) - dc.date.available 3-Jan-2018 16:20:31 (UTC+8) - dc.date.issued (上傳時間) 3-Jan-2018 16:20:31 (UTC+8) - dc.identifier (Other Identifiers) G0104753026 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/115463 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 資訊科學學系 zh_TW dc.description (描述) 104753026 zh_TW dc.description.abstract (摘要) 隨著社群媒體的普及，新聞媒體與意見領袖逐漸重視在社群媒體上以貼文方式發佈新聞資訊，社群媒體成為許多使用者會接收新聞與重大事件的主要管道且透過社群媒體的評論、分享與按讚等互動機制表達立場，這些即時互動行為是傳統媒體缺乏的機制，如何分析也是研究上的挑戰。本研究將針對Facebook上的貼文與互動行為進行分析，提供一款互動視覺化系統，找出貼文資料集中相似的貼文群集以及隨著時間推移下貼文屬性的變化，進一步瞭解Facebook上使用者、貼文與重大事件之間的相互影響。由於Facebook上的貼文與互動行為具多維度屬性，我們透過降維演算法將大量的貼文以二維散佈圖呈現，達到將相似貼文分群的效果。另外，我們設計了一種視覺化呈現方法，「Time Block」，突顯出時間的推移下貼文屬性的變化，藉此觀察出貼文資料集是否存在特定的模式。最後提供即時互動的操作介面，以及貼文屬性以及關鍵字兩者的統計，藉此連接到貼文集的屬性與時間的分佈關係，協助以視覺化方式進行探索與分析。最後，透過案例分析與使用者測試呈現此視覺化探索工具的優缺點。 zh_TW dc.description.abstract (摘要) Social media becomes an essential medium for broadcast news. News media and option leader post information and people love to receive news and interactive using comment and likes to feedback. It is a research challenge to analysis this massive amount interactive behavior data in social media. In this paper, we propose an interactive visualization system to explore on the posts and interactions on Facebook. This system can help a user to find out the similar interactive behavior cluster and the trend of time-varying attributes to understand how the users, posts, and a big event to affect each other. Facebook Posts and interactive behavior contains multiple dimensional attributes; we adopt the dimensional reduce algorithm and 2D scatter plot to present the cluster in the spatial domain. Then, we design a time-varying visualization method, "Time Block,` can highlight the changing attributes and observe the unique pattern in the time domain. Also, we design a real-time interactive interface to connect the cluster and trend visualization with additional keyword distribution and attribute statistics. Finally, we use case study and user study to demonstrate the advantage of the proposed system. en_US dc.description.tableofcontents 摘要 iAbstract ii目錄 iii圖目錄 v第一章 緒論 11.1 研究動機與目的 11.2 問題描述 21.3 論文貢獻 31.4 論文章節架構 4第二章 相關研究 52.1 社群媒體資料視覺化 52.2 多維度資料視覺化 72.3 時序性資料視覺化 9第三章 研究方法與步驟 113.1 系統架構 113.2 資料撈取與整合 123.3 多維度資料視覺化 153.4 時序性資料視覺化 203.5 互動機制設計 233.5.1 貼文散佈圖的互動操作 243.5.2 時間區塊的互動操作 27第四章 實驗結果與分析 304.1 實作與實作環境 314.2 個案研究 314.2.1 單一粉絲專頁觀察 314.2.2 兩個粉絲專頁比較觀察 354.3 初步使用者測試 414.4 使用者測試 45第五章 結論、限制與未來展望 525.1 結論 525.2 限制 535.3 未來工作 53參考文獻 54附錄 57 zh_TW dc.format.extent 6089398 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0104753026 en_US dc.subject (關鍵詞) 資料視覺化 zh_TW dc.subject (關鍵詞) 多維度資料 zh_TW dc.subject (關鍵詞) 時序性資料 zh_TW dc.subject (關鍵詞) 社群網路 zh_TW dc.title (題名) 針對社群媒體上的趨勢變化之視覺化探索工具 zh_TW dc.title (題名) A study of visual exploration tool for comparing trend en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) [1]B. Bach, N. Henry‐Riche, T. Dwyer, T. Madhyastha, J. D. Fekete, and T. Grabowski, "Small MultiPiles: Piling time to explore temporal patterns in dynamic networks," in Computer Graphics Forum, 2015, vol. 34, no. 3, pp. 31-40: Wiley Online Library.[2]B. Bach, C. Shi, N. Heulot, T. Madhyastha, T. Grabowski, and P. Dragicevic, "Time curves: Folding time to visualize patterns of temporal evolution in data," IEEE transactions on visualization and computer graphics, vol. 22, no. 1, pp. 559-568, 2016. [3]R. Blanch, R. Dautriche, and G. Bisson, "Dendrogramix: A hybrid tree-matrix visualization technique to support interactive exploration of dendrograms," in Visualization Symposium (PacificVis), 2015 IEEE Pacific, 2015, pp. 31-38: IEEE.[4]N. Cao, C. Shi, S. Lin, J. Lu, Y.-R. Lin, and C.-Y. Lin, "TargetVue: Visual analysis of anomalous user behaviors in online communication systems," IEEE transactions on visualization and computer graphics, vol. 22, no. 1, pp. 280-289, 2016.[5]J. Chen, A. M. MacEachren, and D. J. Peuquet, "Constructing overview+ detail dendrogram-matrix views," IEEE transactions on visualization and computer graphics, vol. 15, no. 6, pp. 889-896, 2009.[6]Q. Cui, M. O. Ward, and E. A. Rundensteiner, "Enhancing scatterplot matrices for data with ordering or spatial attributes," in Electronic Imaging 2006, 2006, pp. 60600R-60600R-11: International Society for Optics and Photonics.[7]M. Hu, K. Wongsuphasawat, and J. Stasko, "Visualizing Social Media Content with SentenTree," IEEE Transactions on Visualization and Computer Graphics, vol. 23, no. 1, pp. 621-630, 2017.[8]M. Kim, K. Kang, D. Park, J. Choo, and N. Elmqvist, "Topiclens: Efficient multi-level visual topic exploration of large-scale document collections," IEEE Transactions on Visualization and Computer Graphics, vol. 23, no. 1, pp. 151-160, 2017.[9]B. Kondo and C. Collins, "Dimpvis: Exploring time-varying information visualizations by direct manipulation," IEEE transactions on visualization and computer graphics, vol. 20, no. 12, pp. 2003-2012, 2014.[10]L. v. d. Maaten and G. Hinton, "Visualizing data using t-SNE," Journal of Machine Learning Research, vol. 9, no. Nov, pp. 2579-2605, 2008.[11]S. Rufiange and M. J. McGuffin, "DiffAni: Visualizing dynamic graphs with a hybrid of difference maps and animation," IEEE Transactions on Visualization and Computer Graphics, vol. 19, no. 12, pp. 2556-2565, 2013.[12]J. Stasko, R. Catrambone, M. Guzdial, and K. McDonald, "An evaluation of space-filling information visualizations for depicting hierarchical structures," International journal of human-computer studies, vol. 53, no. 5, pp. 663-694, 2000.[13]J. Stasko and E. Zhang, "Focus+ context display and navigation techniques for enhancing radial, space-filling hierarchy visualizations," in Information Visualization, 2000. InfoVis 2000. IEEE Symposium on, 2000, pp. 57-65: IEEE.[14]F. Viégas et al., "Google+ ripples: A native visualization of information flow," in Proceedings of the 22nd international conference on World Wide Web, 2013, pp. 1389-1398: ACM.[15]M. Wattenberg, F. Viégas, and I. Johnson, "How to Use t-SNE Effectively," Distill, vol. 1, no. 10, p. e2, 2016.[16]F. Wickelmaier, "An introduction to MDS," Sound Quality Research Unit, Aalborg University, Denmark, vol. 46, 2003.[17]X. Yuan, D. Ren, Z. Wang, and C. Guo, "Dimension projection matrix/tree: Interactive subspace visual exploration and analysis of high dimensional data," IEEE Transactions on Visualization and Computer Graphics, vol. 19, no. 12, pp. 2625-2633, 2013.[18]F. Zhou et al., "Dimension reconstruction for visual exploration of subspace clusters in high-dimensional data," in Pacific Visualization Symposium (PacificVis), 2016 IEEE, 2016, pp. 128-135: IEEE.[19]MUNZNER, Tamara. Visualization analysis and design. CRC press, 2014.[20]https://developers.facebook.com/docs/graph-api/advanced/rate-limiting[21]https://github.com/yanyiwu/nodejieba/blob/master/README_EN.md zh_TW
