拜網路的普及所賜，Facebook是現今最火紅的社交服務平台，使用人數也成驚人的指數成長。水能載舟，亦能覆舟，Facebook 所提供的社團功能除了能夠幫助使用者拉近彼此的距離外，卻也被不肖人士作為詐騙的新手法。為了杜絕該情況發生，因此提出一個新的服務幫助使用者避免受騙的情況發生。
此服務會透過使用者授予該應用程式相關權限後，嘗試去取得使用者社團的內容。透過這些擷取的內容，我們經過初步分析，再將這些資訊放入我們用來分類的模型。我們會將分類結果判斷該社團是否為廣告性社團。而我們將定期為使用者的社團做分析處理，並將結果以清單方式回傳給使用者，並加入適當建議，讓使用者更能清楚地了解潛在風險。而為了瞭解錯誤率等情況，我們會將該應用程式作實驗，並透過手動檢查與其他的應用程式作驗證，幫助我們更加瞭解應用程式的分析情形。最後，我們希望使用者能夠對於廣告性社團更有警覺心，也希望每個使用者在臉書上有更好的使用經驗。

With the popularity of Facebook, it has become the newest platform of spamming distributor. Our target is focusing on Facebook group pages, which is occupied with spam messages. With the huge amount of spam, user might feel disturbed, and even confront personal data leak. Therefore, it is necessary to solve this problem. We implement SVM algorithms to support our text filtering mechanism. And according to the group's features to evaluate each one. Lastly, based on the results, to send the appropriate advices to the users. We hope each user could have a better experience on Facebook.

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