In this paper, we describe the results of gender identification from Team DUBL. We used a topic modeling approach for identifying the author’s gender based on his/her written texts. The model was trained on the RusProfiling PAN 2017 Twitter Corpus that contains data in the Russian language. Themodel has been evaluated on texts of other genres, including texts such as letters to a friend, online...

Conventional approaches to gender classification much rely on a large scale of labeled data, which is normally hard and expensive to obtain. In this paper, we propose a co-training approach to address this problem in gender classification. Specifically, we employ both non-interactive and interactive texts, i.e., the message and comment texts, as two different views in our cotraining approach to...

Fusing textual information, as type of information fusion, has been great significance to those interested in making informative texts out the existing ones. The main idea behind text like any other is merge partial from different sources such a way that outcome can hold reasonably high relevance with regard certain objectives. In this paper, fuzzy framework proposed for generation, according w...

Much recent work on gender has emphasized how ideas of male and female differences underlie cultural assumptions about appropriate social relations, behavior, institutions and knowledge. This study focuses on the specific ways that anatomy texts for medical students in the United States have presented male and female anatomy between 1890 and 1989, using both numerical data and analysis of textu...

The aim of the present study was to investigate the importance of skopos in the translation of political texts from English into Persian. To do this, 30 Iranian translators were conveniently selected and equally divided into the in-house and freelance translators. They were asked to translate a translation test encompassing 10 short political texts that were extracted from English news websites...