In this paper, we are interested in defining the gender of blogger while using only texts written from bloggers. For that purpose, we offer a number of features based on specific words, which were categorized into classes. For each blog, a score is calculated based on these characteristics, thereby determining the gender of its author. The evaluation was made on a corpus of 681,288 Blogs (140 million words) tagged as men or women. In our work, this collection will be taken as a reference. The obtained results show gender detection over 82% compared to the referenced collection.
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