當在作故事產生時，如果沒有去考慮友誼問題時，某些故事情節可能會變得不合理或是彈性受到限制。我提出一個友誼解決方案可以提供一個故事情節來達成需求的友誼變化。我使用人力資源外包的方式來蒐集故事，然後將它們轉換為可程式處理的形式。接著根據他們的因果關係以及意義上的協同性進行切割以產生片段，然後估計這些片段所造成的友誼衝擊以及片段發生時候的友誼度。最後，藉由把這些片段放在適合的友誼度上以及用這些片段來更新當前的友誼程度，我們就可以產生出新的故事了。在實驗中，我們要求填卷者將一個人工故事、一個模型產生故事以及一個隨機產生故事作合理度的排序。實驗的結果顯示模型產生的故事和人工故事的表現是接近的。另一方面，這個模型也的確有其通用性。

The story plots without considerations about social friendship may be not reasonable or its feasibility may be limited. I propose a friendship resolution that can provide a plot that which accomplishes the required friendship change. I collect stories from human outsourcing, and transit the stories into a designed presentation which could be processed by program. Then I slice the stories according to the inner event’s causality or co-meaning relation and extract story fragments. The “friendship impact” and “friendship level to appear” are estimated. Finally, we can generate the plot by put fragments in appropriate friendship level and estimate the current friendship with the friendship impact. The experiment which ask form fillers to sort the rationality between a human-written, a model generated and a random generated stories has shown that the model generated story was even better than human-written ones. And this model is generic to handle requires in open domain.

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