網路科技的蓬勃發展使網路成為新型態的資訊分享平台，社群問答網站也應運而生，社群問答網站允許使用者以自然語言的方式提出問題並獲得其他使用者詳細的回答，使用者也可搜尋過往問答紀錄觀看是否有相似的問題及回答，因網站中的答案是由使用者自行提供，鑒於使用者的知識限制及自然語言表達方式過於複雜，答案品質會有極大落差。
　　另外，近年來行銷方式改變，廠商會徵求寫手於各大社群網站、論壇及部落格等網站中撰寫推銷自家產品及服務或攻擊對手的文章，目前社群問答網站中也逐漸出現這些廣告文章，使用者須要花費大量時間過濾掉廣告答案及低品質的答案，才能獲得真正符合其需求的答案。過往對社群問答網站答案品質的研究大多將答案分為高品質與低品質兩個類別，但因廣告答案通常會是推銷與問題相關的產品，若採用過往相關研究的方法，可能會因為答案與問題高度相關而將廣告答案判斷為高品質答案，使分類結果不如預期。過往研究亦指出不同問題類型對於答案品質的定義會有不同。因此本研究欲過濾出社群問答網站中的廣告答案，並於不同問題類型下分析答案品質，將答案分為高品質答案、低品質答案及廣告答案三類，讓使用者閱讀答案時能更有效率。實驗結果顯示考慮問題類型的答案品質分析時準確率為0.842，於答案品質分析前先進行廣告答案識別有助於降低將廣告答案誤判為高品質答案的比例。

The rapid development of Internet makes it a new information sharing platform. Community question answering websites emerge as the time required. Users can post and answer questions in the community. Since the answers are devoted by volunteers, due to the knowledge limitation of users and the complexity of natural language expression, the answer quality varies greatly.
Excepting to the quality of answers, some answers are posted by the writers who are paid to post advertising content in social media for commercial purpose. The community question answering become the targets of those campaigns recently. Several researches try to classify the answers in the community question answering website into high-quality and low-quality. However, using those research methods, the spam answer may be misjudged as high-quality answers because the spam answers are usually highly related to the question.
In order to ignore the spam answers and suggest the real high-quality answers, this study wants to filter the spam answers and evaluate the quality of the non-spam answers under different question types. The answers will be divided into high-quality, low-quality and spam. The results show that the accuracy of our quality analysis method is 0.842, and doing spam filtering before answer quality analysis can reduce the proportion of misjudging spam answers as high-quality answers.

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