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Text-based analysis methods allow to reveal privacy relevant author attributes such as gender, age and identify of the text's author. Such methods can compromise the privacy of an anonymous author even when the author tries to remove privacy sensitive content. In this paper, we propose an automatic method, called Adversarial Author Attribute Anonymity Neural Translation (A^4NT), to combat such text-based adversaries. We combine sequence-to-sequence language models used in machine translationarXiv:1711.01921v3 fatcat:s3wnqeufrbcgtcp4pntljugff4