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Short message communication media, such as mobile and microblogging social networks, have become attractive platforms for spammers to disseminate unsolicited contents. However, the traditional content-based methods for spam detection degraded in performance due to many factors. For instance, unlike the contents posted on social networks like Facebook and Renren, SMS and microblogging messages have limited size with the presence of many domain specific words, such as idioms and abbreviations. In addition, microblogging messages are very unstructured and noisy. These distinguished characteristics posed challenges to existing email spam detection models for effective spam identification in short message communication media. The state-of-the-art solutions for social spam accounts detection have faced different evasion tactics in the hands of intelligent spammers. In this paper, a unified …