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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/103146

    Title: 社群網路服務上之情緒關懷系統
    Other Titles: An Emotion Care System on Social Networking Services
    Authors: 許輝煌
    Contributors: 淡江大學資訊工程學系
    Keywords: 社群網路;情緒分析;語意分析;眾包;關懷指標;Social Networks;Emotion Analysis;Semantic Analysis;Crowdsourcing;Attention Index
    Date: 2012-08
    Issue Date: 2015-05-19 16:47:44 (UTC+8)
    Abstract: 社群網路服務是現今人們保持聯繫的一個重要管道。從朋友的留言,使用者可以知 道他的朋友們最近的活動、新聞和情緒狀態。保持友誼最重要的就是在適當的時間表達 我們對於朋友的關心。在本研究中,我們希望開發一個可以過濾、分析朋友們在社群網 路服務上的留言,來了解哪些朋友是需要即時的關懷。選定的朋友在Facebook 塗鴉牆上 的留言會先被過濾,來排除由遊戲或其他應用程式所留的訊息。過濾後所留下來的留言 再被分類為八個類別,包含六個情緒類別、特殊事件和其他。這些留言中字詞和表情符 號的情緒類別會被進一步計算來得到一個本研究提出的關懷指標。選定的朋友們最後會 依據這個關懷指標的大小來進行排序。高關懷指標的朋友就是需要使用者去適時表達關 懷的朋友。這樣的結果將會使用圖形、視覺化的介面來呈現。使用者可以直接連結到某 位朋友的相關留言,來針對該位朋友的留言進行接續的留言。在本研究中,我們將開發 一個情緒分類的伺服器、開發一個Facebook 遊戲來應用眾包對情緒詞彙做分類、定義一 個適切的情緒關懷指標、開發一個Facebook 應用程式來作情緒關懷、以及一個智慧型手 機應用程式來讓使用者可以在行動環境下使用本系統。
    Social networking services are an important channel for people to keep in contact nowadays. Through the messages posted by friends, the user is able to know his/her friends’ recent activities, news and emotion status. To show our cares to friends at a proper time is essential in keeping the friendship. In this research, we aimed at developing a system that can screen and analyze the messages posted by friends on social networking services to know which friends need instant attention/care. The posts on Facebook Wall of a friend are filtered first to obtain the messages by the friend, excluding the posts by games or other applications. The obtained messages are then classified into one of eight categories, including six emotion categories, special events, and others. The category information of the terms in the messages is then further analyzed for a proposed attention index. After the attention indices of the selected friends are decided, they are ranked by the indices. The ones with higher attention indices need the user to show his/her care in a timely manner. The desired information can be visualized in a graphical interface. The user can easily connect to relevant posts of a friend to leave follow-up messages. In this research, we will develop an emotion classification server, a Facebook game for emotion terms classification through crowdsourcing, a proper attention index for emotion care, a Facebook application for emotion care, and a mobile phone application for mobile access to the system.
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Research Paper

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