推特是一個近幾年來非常熱門的社交網路和微網誌服務。在推特上，使用者可以在推文中使用主題標籤來表示這篇推文的主題。然而，因為使用者可以沒有限制的創建一個新的主題標籤，所以在推特上有很多不同類型的主題標籤。有些主題標籤很特別，所以我們很難知道這些主題標籤是什麼意思。出自這個原因，我們的目標是將主題標籤分到特定的類別。這不但可以幫助使用者更了解主題標籤的意思，也可以幫助他們尋找他們有興趣的話題。為了定位這個問題，我們根據使用者間的互動對每個主題標籤建立了訊息擴散圖，並擷取其特徵。由於主題標籤很多樣化，所以我們從主題標籤內容特徵和圖拓樸特徵這兩個觀點上探討特徵。接著我們從訊息轉推圖和擴散圖中萃取特徵用於主題標籤的分類。在主題標籤的分類上，我們的結果顯示擴散圖的特性是很重要的。此外根據我們的研究結果，擴散圖比轉推圖更適合用來描繪主題標籤的特性。

Twitter is a social networking and micro-blogging service which has become popular in recent years. In Twitter, users can use hashtags to represent the topic of a tweet. Nevertheless, there are too many hashtags because users can create a new hashtag without any restriction. Some hashtags are too special so that it is difficult to understand what they are about. For this reason, our goal is to classify hashtags into specific topics that are helpful for users to understand the topic and meaning of a tweet. It can help users not only understanding the meaning of hashtags but also searching for topics that they are interested in. To address this problem, we build the diffusion graph for each hashtag according to the interactions among users. Due to the variety of hashtags, we explored features from the perspectives of hashtag content features and graph topology features. After that, we extract these features from the retweet graph and the diffusion graph for hashtag classification. Our results show that the characteristics of diffusion graph are important and effective in hashtag classification. Besides, the diffusion graph is more suitable for representing hashtag characteristics than the retweet graph.

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