隨著社群網站的大量崛起，人們在網路上的行為從早期的單方面獲得資訊，慢慢轉變到與他人的網頁互動，以至於到最近的發展成社群（Community）關係。網路使用者對虛擬社群的好奇，導致了相關社群網站的蓬勃發展。近年來對於社群網路的研究日漸興盛，各個研究領域都分別以其擅長的角度嘗試切入，想了解為何社群網路如此快速的崛起、社群網路形成的各種架構或是社群網路上的大量資料呈現的資訊以及其分析等等。 社群網站滿足了人們期待與其他人產生互動、情感維繫以及得到更多資訊的需要，提供了一個虛擬空間，讓關心相同主題的使用者群聚在一起並且分享資訊。無論是想與他人互動，或是情感維繫以及渴望得到資訊，這些動機皆與人的情感表現息息相關，本研究即是採用情感的角度，來觀察社群中的特定行動者與其網路。 有關世界城市網路的研究目前並不多見，本研究嘗試以城市為社會網路中的行動者角色，研究一個由網路相片分享構築成的特殊社群網站Flickr。利用相片可忠實呈現拍攝者與被拍攝者情感的特性，以「城市」與「情感」兩大基礎來觀察此社群，嘗試構築出一個有關世界城市情感面向的網路關係。根據本研究目的，我們將建立「城市－情感共現網路」，來發掘世界主要城市之間隱含的連結與關係，或是其隱藏的情感表現。 / Along with considerable growth of social network websites, people’s actions on internet changed slowly from acquiring information to exchanging information and interacting with other people via web pages, and eventually this change has created a so-called “community relationship” on line. This blossom of relevant social network websites resulted from internet users’ curiosity about the invented virtual community. Numerous researchers in each relevant field have donated themselves into analysis and researches aiming to understand the reasons why all kinds of community websites have been created so quickly, how these communities have been structured, how the information and data underlying these websites have been presented and analyzed. The goal of this paper is to dig out links and relations between big cities worldwide and human emotions in these cities via community websites. We tried to analyze a unique community website “Flickr” that functions on the base of uploading pictures only. We categorized the pictures on Flickr on two pillar axes, “Region” and “Emotion”, as the emotions of photo shooters and personages have been detailed and recorded by these pictures. By the above categories, We drew a map of emotions in cities that will reveal a 2-mode network of emotions and cities.

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".