由於社交網站的成功，相關的分析研究已被廣泛研究，在這些研究中，社群影響力是重要和熱門的主題。我們利用社群影響力模型來預測和學習影響力傳播過程，雖然先前已有人提出若干個影響力模型，然而，這些傳統的影響力模型都只將節點分為兩種狀態，活躍和不活躍的狀態，這個策略導致了一些問題，以前的模型只考慮正向影響力的存在，另外，如果不活躍的節點被成功的影響成活躍的節點，這些節點不能再返回到不活躍的節點，在我們的模型中，我們不僅改善了上述的限制，還在我們的模型中使用了新的傳遞影響力方式。我們的多型態影響力模型提出了五個代表性的影響力狀態，透過我們的傳遞方式，社群影響力可能會隨時間而減弱。最後，我們使用精準度的測量與相關影響力模型進行比較，我們的影響力模型優於只有兩種狀態的其他影響力模型，此外，我們還預測使用五個狀態的精準度結果，透過實驗結果，可觀察到多型態節點在社群網路裡的重要性。

Since the tremendous success of social networking websites, the research on related analysis have widely been studied. Among these research, the social influence is a significant and popular topic. We rely on the social influence model to predict and learn the influence diffusion process. There are several influence models proposed before. However, traditional models only categorize nodes into two types of state, active and inactive. This strategy causes some problems. Previous models only take the positive influence into account. In addition, if the inactive nodes are influenced successfully as active nodes, these active nodes could not return to inactive nodes. In this work, we not only improve above limitations but also propose an novel propagation method in our model. Our model proposes five states to represent the multiple states of influence. By our propagation method, the strength of social influence might be reduced when time elapsed. Eventually, we utilize the measurement of precisions to compare with related models. Our model outperforms than other models with two states. In addition. we predict the result of five states using our model. By means of experiment result, we indicate the importance of multiple states.

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