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題名 Flickr網站上世界商務城市之情感輪廓
Emotional Contours of the Commerce Cities on the Website Flickr
作者 馮成發
Fong, Chen Fa
貢獻者 劉吉軒
Liu, Jyi Shane
馮成發
Fong, Chen Fa
關鍵詞 Flickr
NodeXL
社群網站
城市
相片
顯著標籤
情緒標籤
Flickr
NodeXL
social website
cities
photo
significant tag
emotion tag
日期 2013
上傳時間 10-Feb-2014 14:56:55 (UTC+8)
摘要   近年來電腦科學的進步只能以一日千里來形容,不管在軟體或是硬體方面都有驚人的發展,軟體方面有網際網路Web 2.0技術的興盛及普及,使得人們在分享及交流資訊更加快速且便利,硬體方面則有數位相機和有照相功能智慧型手機的發明,造就了分享資訊很快的從文字模式演變成影音、相片等多媒體模式。Flickr社群網站為目前網路世界裡最重要的相片分享平台,每個人都可以將生活中擁有喜、怒、哀、樂情緒的相片上傳至該網站上與他人分享,而且此網站平台也提供下標籤功能,讓上傳者可以更正確的傳達要分享的情感。如當相片被加註上快樂的標籤,也就代表上傳者對這張相片當時的環境情緒反應為愉快、或甚至於興奮,相反地;當相片被加註上生氣的標籤,就表示該相片給上傳者的情緒反應是不愉快的、或甚至於憤怒。當同一區域(如城市)透過大量情感標籤的累積,自然而然就會呈現出該區域的情感輪廓。

  情緒議題的研究近年來在各知識領域中已被廣泛的討論著,但針對區域性的情緒表現之研究探討似乎還不多。本研究藉由Flickr社群網站的全球性特質,結合Derudder and Taylor兩位學者於2005年提出的「The cliquishness of world cities」研究報告,定義出41個商務活動頻繁城市作為本研究的研究範圍,並應用Flickr社群網站上強大又完整的API介面功能,撰寫Client端程式擷取這些城市在Flickr網站上有加註情緒標籤的相片數共761,854張、其相關的標籤數有21,569,593個,再經由本研究提出的研究方法及步驟,逐一處理這些各城市相片上傳者所加註的大量標籤,就可以找出每個城市各情感象限數量最多的前30個標籤當作顯著標籤。

  最後本研究綜合分析從Flickr網站上取得的大量城市、相片、及顯著標籤相關資料,分別計算出每個城市正負向情感象限的強度百分比,再以正向情感象限強度百分比為基準,定義出這些商務活動頻繁城市的「快樂指數」數值;並利用社會網絡分析軟體NodeXL來觀察各城市、情感性標籤與顯著標籤所呈現的網絡關係。
In recent years, the computer science progress is extremely fast, whether in software or hardware has an alarming growth. The software aspect has the Internet Web 2.0 technology prosperity and popular, causes the people in share and exchange information are faster and convenient. The hardware aspect has the digital cameras and the smartphones invention, causes the share information from the writing pattern to the multimedia patterns very quickly. The Flickr social website is the most important of shared photograph in the network world for currently,everyone can shared the joy, anger, sadness, happy mood photograph by uploading to this website. This website platform also provides the tagging function, lets the uploader can more correct transmission their emotion. When the identical region (such as a city) through a large number of emotional labels cumulatively, naturally will be showing the emotional contours of the region.
Emotional issues have been widespread discussion in various area of knowledge in recent years, but research the performance of emotion for region seems not much. This research because of Flickr social website global special characteristic, combined Derudder and Taylor two scholars to propose "The cliquishness of world cities" research reports in 2005, Defines 41 economics and trade activity frequent city to take this research the study scope.
Finally, this research made a comprehensive analysis by a large number of cities, photos, and significant label information from the Flickr website, and calculates the percentage of each city to the strength of positive and negative emotions quadrant.Then the percentage of positive emotional intensity as a benchmark quadrant, Defines these economics and trade activity frequent city`s "happiness index".
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Coleman, J.S. (1990). Foundations of Social Theory. Cambridge MA. Harvard University Press.
Derudder, B., & Taylor, P. (2005). The Cliquishness of World Cities. Global Networks: A Journal of Transnational Affairs, Vol. 5, No. 1:71-91.
Freeman, L.C. (1979). Centrality in social networks: conceptual clarification. Social Networks, 1 : 215-239.
Gardner, M.P. (1985). Mood States and Consumer Behavior: A Critical Review. Journal of Consumer Research, vol. 12(December), 281-300.
Golder, S.A., & Huberman, B.A. (2006). The Structure of Collaborative Tagging Systems. Journal of Information Science 32, 198-208.
Hammond, T., Hannay, T., Lund, B., & Scott, J. (2005). Social bookmarking tools (i). D-Lib Magazine, 11(4), 1082-9873.
Izard, C.E. (1977). Human emotions. New York: Plenum.
Kipp, M.E. (2006). Exploring the context of user, creator and intermediate tagging in IA Summit 2006, Vancouver, Canada.
Lange, P.G. (2007). Publicly Private and Privately Public: Social Networking on YouTube. Journal of Computer-Mediated Communication, Vol. 13, No. 1, pp.361-380.
Marlow, C., Naaman, M., Boyd, d., & Davis, M. (2006). Position Paper, Tagging, Taxonomy, Flickr, Article, Toread. Proceedings of the Conference on Collaborative Web Tagging Workshop at WWW 2006, Edinburgh, United Kingdom.
Mathes, A. (2004). Folksonomies-Cooperative Classification and Communication Through Shared Metadata. Technical Report. LIS590CMC, Computer Mediated Communication, Graduate School of Library and Information Science, University of Illinois, Urbana-Champaign.
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Plutchik, R. (1980). A Strutural Model of Emotion. In Emotion:A Psycho evolutionary Synthesis, pp.152-172, New York, Harper and Row Publishers
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Russell, J.A. (1980). A Circumplex Model of Affect. Journal of Personality and Social Psychology, 39(December), 1161-1178
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Sen, S., Lam, S.K., Rashid, A.M., Cosley, D., Frankowski, D., Osterhouse, J., Harper, F.M., & Riedl, J. (2006). Tagging, communities, vocabulary, evolution. Proceedings of the 20th Anniversary Conference on Computer Supported Cooperative Work, November 4-8, 2006, Banff, Alberta, Canada.
Smith, G. (2008). Tagging: People-Powered Metadata for the Social Web. San Francisco:New Rider Press.
Tapscott, D., & Williams, A.D. (2006). Wikinomics: How mass collaboration changes everything. New York: Portfolio.
Wartburg, I.V., Teichert, T., & Rost, K. (2005). Inventive progress measured by multi- stage patent citation analysis. Research Policy, 34:1591–1607.
Wasserman, S., & Faust, K. (1994). Social Network Analysis. Methods and Applications. Cambridge. Cambridge University Press.
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林慶文(民96)。以大眾分類法為基礎之網站內容分類架構-以社群書籤網站為例。中原大學資訊管理學系碩士論文,未出版,桃園縣。
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李麗華、許榮望、李富民、黃煜紘、陳志瑋等(民101)。網路標籤變化研究之初探-以台灣熱門網站為例。資訊科技國際期刊第六卷第二期。
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描述 碩士
國立政治大學
資訊科學學系
99971016
102
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0099971016
資料類型 thesis
dc.contributor.advisor 劉吉軒zh_TW
dc.contributor.advisor Liu, Jyi Shaneen_US
dc.contributor.author (Authors) 馮成發zh_TW
dc.contributor.author (Authors) Fong, Chen Faen_US
dc.creator (作者) 馮成發zh_TW
dc.creator (作者) Fong, Chen Faen_US
dc.date (日期) 2013en_US
dc.date.accessioned 10-Feb-2014 14:56:55 (UTC+8)-
dc.date.available 10-Feb-2014 14:56:55 (UTC+8)-
dc.date.issued (上傳時間) 10-Feb-2014 14:56:55 (UTC+8)-
dc.identifier (Other Identifiers) G0099971016en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/63710-
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) 99971016zh_TW
dc.description (描述) 102zh_TW
dc.description.abstract (摘要)   近年來電腦科學的進步只能以一日千里來形容,不管在軟體或是硬體方面都有驚人的發展,軟體方面有網際網路Web 2.0技術的興盛及普及,使得人們在分享及交流資訊更加快速且便利,硬體方面則有數位相機和有照相功能智慧型手機的發明,造就了分享資訊很快的從文字模式演變成影音、相片等多媒體模式。Flickr社群網站為目前網路世界裡最重要的相片分享平台,每個人都可以將生活中擁有喜、怒、哀、樂情緒的相片上傳至該網站上與他人分享,而且此網站平台也提供下標籤功能,讓上傳者可以更正確的傳達要分享的情感。如當相片被加註上快樂的標籤,也就代表上傳者對這張相片當時的環境情緒反應為愉快、或甚至於興奮,相反地;當相片被加註上生氣的標籤,就表示該相片給上傳者的情緒反應是不愉快的、或甚至於憤怒。當同一區域(如城市)透過大量情感標籤的累積,自然而然就會呈現出該區域的情感輪廓。

  情緒議題的研究近年來在各知識領域中已被廣泛的討論著,但針對區域性的情緒表現之研究探討似乎還不多。本研究藉由Flickr社群網站的全球性特質,結合Derudder and Taylor兩位學者於2005年提出的「The cliquishness of world cities」研究報告,定義出41個商務活動頻繁城市作為本研究的研究範圍,並應用Flickr社群網站上強大又完整的API介面功能,撰寫Client端程式擷取這些城市在Flickr網站上有加註情緒標籤的相片數共761,854張、其相關的標籤數有21,569,593個,再經由本研究提出的研究方法及步驟,逐一處理這些各城市相片上傳者所加註的大量標籤,就可以找出每個城市各情感象限數量最多的前30個標籤當作顯著標籤。

  最後本研究綜合分析從Flickr網站上取得的大量城市、相片、及顯著標籤相關資料,分別計算出每個城市正負向情感象限的強度百分比,再以正向情感象限強度百分比為基準,定義出這些商務活動頻繁城市的「快樂指數」數值;並利用社會網絡分析軟體NodeXL來觀察各城市、情感性標籤與顯著標籤所呈現的網絡關係。
zh_TW
dc.description.abstract (摘要) In recent years, the computer science progress is extremely fast, whether in software or hardware has an alarming growth. The software aspect has the Internet Web 2.0 technology prosperity and popular, causes the people in share and exchange information are faster and convenient. The hardware aspect has the digital cameras and the smartphones invention, causes the share information from the writing pattern to the multimedia patterns very quickly. The Flickr social website is the most important of shared photograph in the network world for currently,everyone can shared the joy, anger, sadness, happy mood photograph by uploading to this website. This website platform also provides the tagging function, lets the uploader can more correct transmission their emotion. When the identical region (such as a city) through a large number of emotional labels cumulatively, naturally will be showing the emotional contours of the region.
Emotional issues have been widespread discussion in various area of knowledge in recent years, but research the performance of emotion for region seems not much. This research because of Flickr social website global special characteristic, combined Derudder and Taylor two scholars to propose "The cliquishness of world cities" research reports in 2005, Defines 41 economics and trade activity frequent city to take this research the study scope.
Finally, this research made a comprehensive analysis by a large number of cities, photos, and significant label information from the Flickr website, and calculates the percentage of each city to the strength of positive and negative emotions quadrant.Then the percentage of positive emotional intensity as a benchmark quadrant, Defines these economics and trade activity frequent city`s "happiness index".
en_US
dc.description.tableofcontents 第一章 緒論.................................................1
1.1 簡介...................................................1
1.2 研究背景與動機...........................................1
1.3 研究目的與研究方法........................................3
1.4 研究貢獻................................................5
1.5 論文架構................................................6
第二章 文獻探討..............................................8
2.1 社會網絡分析.............................................8
2.1.1 社會網絡..............................................8
2.1.2 社會網絡分析的原理與意義.................................9
2.1.3 社會網絡分析的特徵.....................................11
2.2 大眾分類法之探討.........................................12
2.3 下標籤(TAGGING)的行為研究................................15
2.3.1 標籤(Tag)...........................................15
2.3.2 下標籤(Tagging)的動機.................................15
2.3.3 下標籤(Tagging)的相關研究..............................17
2.4 情緒理論分析............................................19
2.4.1 情緒的定義...........................................19
2.4.2 情緒的類型...........................................20
第三章 研究方法.............................................24
3.1 研究架構...............................................24
3.2 研究範圍訂定............................................27
3.2.1 尋找Flickr網站上傳相片數量最多的前一百個城市...............27
3.2.2 「The cliquishness of world cities」的世界網路城市分群資訊........................................................30
3.2.3 研究範圍的訂定與世界分布情形.............................34
3.3 研究流程...............................................35
3.3.1 搜尋研究範圍內各城市有「情緒字詞」標籤的相片................35
3.3.2 刪除標籤出現兩個城市(含)名稱以上之相片....................40
3.3.3 以Porter`s Stemming演算法規則處理蒐集到的標籤............41
3.3.4 篩選各城市的「候選顯著標籤」(Candidate Significant Tag)..43
3.3.5 建立「雜訊標籤字典」(Noise Tags Dictionary)............44
3.3.6 建立「同義詞標籤字典」(Synonyms Tags Dictionary)........46
3.3.7 確認研究範圍內各城市情感象限的「顯著標籤」(Significant Tag)......................................................48
3.3.8 利用NodeXL社會網絡分析工具觀察特性.......................49
第四章 研究結果與分析........................................50
4.1 城市、相片及顯著標籤的分佈關係.............................50
4.2 FLICKR網站上各情感象限顯著標籤間的社會網絡關係...............53
4.2.1 第一象限城市與顯著標籤的社會網絡關係......................54
4.2.2 第二象限城市與顯著標籤的社會網絡關係......................56
4.2.3 第三象限城市與顯著標籤的社會網絡關係......................59
4.2.4 第四象限城市與顯著標籤的社會網絡關係......................61
4.3 以標籤雲(TAG CLOUD)呈現每一情感象限顯著標籤.................63
4.4 研究範圍內各城市在FLICKR網站上的情感輪廓分析.................66
第五章 結論與未來研究方向.....................................72
5.1 結論..................................................72
5.1.1 Flickr網站上商務活動頻繁城市「快樂指數」..................72
5.1.2 各情感象限的重要關鍵標籤................................74
5.2 未來研究方向............................................75
5.2.1 搜尋相片時索引關鍵字語言上的變化..........................75
5.2.2 研究方法的延伸應用.....................................75
參考文獻...................................................77
附 錄.....................................................81
附錄一 本研究範圍內41個城市各情感象限顯著標籤....................81
附錄二 以情感象限區分統計各城市顯著標籤的數量....................126
附錄三 研究範圍內每個城市各情感象限強度百分比....................133
zh_TW
dc.format.extent 5194959 bytes-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0099971016en_US
dc.subject (關鍵詞) Flickrzh_TW
dc.subject (關鍵詞) NodeXLzh_TW
dc.subject (關鍵詞) 社群網站zh_TW
dc.subject (關鍵詞) 城市zh_TW
dc.subject (關鍵詞) 相片zh_TW
dc.subject (關鍵詞) 顯著標籤zh_TW
dc.subject (關鍵詞) 情緒標籤zh_TW
dc.subject (關鍵詞) Flickren_US
dc.subject (關鍵詞) NodeXLen_US
dc.subject (關鍵詞) social websiteen_US
dc.subject (關鍵詞) citiesen_US
dc.subject (關鍵詞) photoen_US
dc.subject (關鍵詞) significant tagen_US
dc.subject (關鍵詞) emotion tagen_US
dc.title (題名) Flickr網站上世界商務城市之情感輪廓zh_TW
dc.title (題名) Emotional Contours of the Commerce Cities on the Website Flickren_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) Batra, R., & Stayman, D.M. (1990). The Roll of Mood in Advertising Effectiveness, Journal of Consumer Research, 17 (September), 203-214.
Coleman, J.S. (1990). Foundations of Social Theory. Cambridge MA. Harvard University Press.
Derudder, B., & Taylor, P. (2005). The Cliquishness of World Cities. Global Networks: A Journal of Transnational Affairs, Vol. 5, No. 1:71-91.
Freeman, L.C. (1979). Centrality in social networks: conceptual clarification. Social Networks, 1 : 215-239.
Gardner, M.P. (1985). Mood States and Consumer Behavior: A Critical Review. Journal of Consumer Research, vol. 12(December), 281-300.
Golder, S.A., & Huberman, B.A. (2006). The Structure of Collaborative Tagging Systems. Journal of Information Science 32, 198-208.
Hammond, T., Hannay, T., Lund, B., & Scott, J. (2005). Social bookmarking tools (i). D-Lib Magazine, 11(4), 1082-9873.
Izard, C.E. (1977). Human emotions. New York: Plenum.
Kipp, M.E. (2006). Exploring the context of user, creator and intermediate tagging in IA Summit 2006, Vancouver, Canada.
Lange, P.G. (2007). Publicly Private and Privately Public: Social Networking on YouTube. Journal of Computer-Mediated Communication, Vol. 13, No. 1, pp.361-380.
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