隨著Facebook，Twitter，微博等社群平台的發展，以及網路、智慧型手機等行動裝置的普及，使用者獲取資訊的方式已經被改變。在過去，一般使用者只能作為資訊的消費者，單方面的透過新聞媒體，報章雜誌等管道來吸收資訊。現在，使用者能夠透過社群平台發表動態，而這些動態通常會反映到使用者對於時事的看法以及意見。甚至也有可能領先於新聞媒體，發表實際發生於世上的事件。根據我們過去的觀察和經驗，不同類型的事件會有著不同傳播的方式。因此，透過分析使用者傳播資訊的行為，可以對事件進行分類。本研究提出利用concept-based Evolving Social Graph Sequences(cEGS)來分析事件的傳播方式，將社群網路上的事件分成六大類別：Sport、Entertaniment、Liife Activity、Yearly Event、Political以及News。實驗結果顯示，本研究所提出的方法不但有高達八成的查全率(Recall)，而且在信心程度高於一定標準之下，可以達到非常高的查準率(Precision)。

Recently, social networks have become extremely popularity and generated a tremendous amount of content by users. This user-generated content can naturally reflect real-world events as they happen. Here users act as an important role for information propagation through social networks. The goal of this work is to identify event class by its propagation behavior through social network. ``Concept-based evolving graph sequences'' (cEGS) is utilized to verify information propagation trends of events. The experimental results demonstrates our approach successes in classifying events into six classes by the analysis of cEGS.

1 Introduction 1

2 Related work 4

3 Methodology 7

4 Experiment 21

5 Conclusion and Future Work 27

References 28

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